
. 
. *****************************************************************************************************************
> *
. * Weights
. *****************************************************************************************************************
> *
. 
. sum weight_genpop_2020Sep

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
weight_gen~p |      5,900           1    .5350276   .2155166   5.655163

. sum weight_genpop_2020Nov

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
we~p_2020Nov |      4,943           1    .7223314   .1320332   7.020961

. 
. *****************************************************************************************************************
> *
. * Outcome variable
. *****************************************************************************************************************
> *
. 
. codebook presvote_2020Nov

-------------------------------------------------------------------------------------------------------------------
presvote_2020Nov                                                              2020 Presidential vote, post-election
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: Q12_2020Nov

                 Range: [1,9]                         Units: 1
         Unique values: 5                         Missing .: 7,574/12,517

            Tabulation: Freq.   Numeric  Label
                        1,743         1  Donald Trump
                        2,629         2  Joe Biden
                          141         3  Someone else
                           22         4  Did not vote for President
                          408         9  not asked
                        7,574         .  

. recode   presvote_2020Nov (1=0 "Trump") (2=1 "Biden") (3/max=.), gen(VOTEBT)
(4,943 differences between presvote_2020Nov and VOTEBT)

. tab      presvote_2020Nov VOTEBT, mi

                      | RECODE of presvote_2020Nov (2020
                      |        Presidential vote,
    2020 Presidential |          post-election)
  vote, post-election |     Trump      Biden          . |     Total
----------------------+---------------------------------+----------
         Donald Trump |     1,743          0          0 |     1,743 
            Joe Biden |         0      2,629          0 |     2,629 
         Someone else |         0          0        141 |       141 
Did not vote for Pres |         0          0         22 |        22 
            not asked |         0          0        408 |       408 
                    . |         0          0      7,574 |     7,574 
----------------------+---------------------------------+----------
                Total |     1,743      2,629      8,145 |    12,517 

. 
. *****************************************************************************************************************
> *
. * Key predictors
. *****************************************************************************************************************
> *
. 
. * Feeling thermometer ratings [continuous]
. 
. clonevar FTIMMIG = ft_immig_2020Sep
(6,617 missing values generated)

. clonevar FTWHITE = ft_white_2020Sep
(6,617 missing values generated)

. clonevar FTBLACK = ft_black_2020Sep
(6,617 missing values generated)

. clonevar FTHISPN = ft_latino_2020Sep
(6,617 missing values generated)

. clonevar FTASIAN = ft_asian_2020Sep
(6,617 missing values generated)

. 
. recode FTIMMIG FTWHITE FTBLACK FTHISPN FTASIAN (min/-1 101/max = .)
(267 changes made to FTIMMIG)
(179 changes made to FTWHITE)
(182 changes made to FTBLACK)
(248 changes made to FTHISPN)
(287 changes made to FTASIAN)

. sum    FTIMMIG FTWHITE FTBLACK FTHISPN FTASIAN

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     FTIMMIG |      5,633     67.4953    25.72665          0        100
     FTWHITE |      5,721    69.45726    23.89709          0        100
     FTBLACK |      5,718    72.53288     24.6022          0        100
     FTHISPN |      5,652    73.05343    23.04263          0        100
     FTASIAN |      5,613    73.42045    22.80716          0        100

. 
. * Feeling thermometer ratings [absolute]
. 
. recode ft_immig_2020Sep  (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTIMMIG5)
(5,857 differences between ft_immig_2020Sep and FTIMMIG5)

. recode ft_white_2020Sep  (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTWHITE5)
(5,868 differences between ft_white_2020Sep and FTWHITE5)

. recode ft_black_2020Sep  (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTBLACK5)
(5,853 differences between ft_black_2020Sep and FTBLACK5)

. recode ft_latino_2020Sep (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTHISPN5)
(5,871 differences between ft_latino_2020Sep and FTHISPN5)

. recode ft_asian_2020Sep  (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTASIAN5)
(5,873 differences between ft_asian_2020Sep and FTASIAN5)

. 
. label define FT5 0 "0/25" 1 "26/49" 2 "50" 3 "Missing" 4 "51/75" 5 "76/99" 6 "100"

. 
. label values FTIMMIG5 FTWHITE5 FTBLACK5 FTHISPN5 FTASIAN5 FT5

. tab1         FTIMMIG5 FTWHITE5 FTBLACK5 FTHISPN5 FTASIAN5

-> tabulation of FTIMMIG5  

  RECODE of |
ft_immig_20 |
      20Sep |
   (Feeling |
thermometer |
        for |
immigrants) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        444        7.53        7.53
      26/49 |        574        9.73       17.25
         50 |        518        8.78       26.03
    Missing |        267        4.53       30.56
      51/75 |      1,548       26.24       56.80
      76/99 |      2,088       35.39       92.19
        100 |        461        7.81      100.00
------------+-----------------------------------
      Total |      5,900      100.00

-> tabulation of FTWHITE5  

  RECODE of |
ft_white_20 |
      20Sep |
   (Feeling |
thermometer |
  for white |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        278        4.71        4.71
      26/49 |        591       10.02       14.73
         50 |        626       10.61       25.34
    Missing |        179        3.03       28.37
      51/75 |      1,501       25.44       53.81
      76/99 |      2,261       38.32       92.14
        100 |        464        7.86      100.00
------------+-----------------------------------
      Total |      5,900      100.00

-> tabulation of FTBLACK5  

  RECODE of |
ft_black_20 |
      20Sep |
   (Feeling |
thermometer |
  for Black |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        298        5.05        5.05
      26/49 |        436        7.39       12.44
         50 |        496        8.41       20.85
    Missing |        182        3.08       23.93
      51/75 |      1,411       23.92       47.85
      76/99 |      2,392       40.54       88.39
        100 |        685       11.61      100.00
------------+-----------------------------------
      Total |      5,900      100.00

-> tabulation of FTHISPN5  

  RECODE of |
ft_latino_2 |
     020Sep |
   (Feeling |
thermometer |
 for Latino |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        226        3.83        3.83
      26/49 |        415        7.03       10.86
         50 |        495        8.39       19.25
    Missing |        248        4.20       23.46
      51/75 |      1,499       25.41       48.86
      76/99 |      2,398       40.64       89.51
        100 |        619       10.49      100.00
------------+-----------------------------------
      Total |      5,900      100.00

-> tabulation of FTASIAN5  

  RECODE of |
ft_asian_20 |
      20Sep |
   (Feeling |
thermometer |
  for Asian |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        196        3.32        3.32
      26/49 |        386        6.54        9.86
         50 |        533        9.03       18.90
    Missing |        287        4.86       23.76
      51/75 |      1,417       24.02       47.78
      76/99 |      2,483       42.08       89.86
        100 |        598       10.14      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. 
. * Feeling thermometer ratings [relative]
. 
. gen     FTIMM3 = 9

. replace FTIMM3 = 1 if (FTIMMIG >= 0 & FTIMMIG  <  50) & (FTIMMIG < FTWHITE) & (FTIMMIG < FTBLACK) & (FTIMMIG < FT
> HISPN) & (FTIMMIG < FTASIAN)
(599 real changes made)

. replace FTIMM3 = 3 if (FTIMMIG > 50 & FTIMMIG <= 100) & (FTIMMIG > FTWHITE) & (FTIMMIG > FTBLACK) & (FTIMMIG > FT
> HISPN) & (FTIMMIG > FTASIAN)
(609 real changes made)

. replace FTIMM3 = 2 if (FTIMMIG == FTWHITE) & (FTIMMIG == FTBLACK) & (FTIMMIG == FTHISPN) & (FTIMMIG == FTASIAN) 
(7,106 real changes made)

. replace FTIMM3 = 8 if FTIMMIG == . | FTWHITE == . | FTBLACK == . | FTHISPN == . | FTASIAN == .
(7,032 real changes made)

. replace FTIMM3 = . if weight_genpop_2020Sep == .
(6,617 real changes made, 6,617 to missing)

. tab     FTIMM3

     FTIMM3 |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        567        9.61        9.61
          2 |        371        6.29       15.90
          3 |        609       10.32       26.22
          8 |        415        7.03       33.25
          9 |      3,938       66.75      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. label   define FTIMM3 1 "Cold to immigrants" 2 "Indifferent to immigrants" 3 "Warm to immigrants" 8 "Missing" 9 "
> Residual" 

. label   values FTIMM3 FTIMM3

. tab     FTIMM3

                   FTIMM3 |      Freq.     Percent        Cum.
--------------------------+-----------------------------------
       Cold to immigrants |        567        9.61        9.61
Indifferent to immigrants |        371        6.29       15.90
       Warm to immigrants |        609       10.32       26.22
                  Missing |        415        7.03       33.25
                 Residual |      3,938       66.75      100.00
--------------------------+-----------------------------------
                    Total |      5,900      100.00

. 
. * use for spot checking coding
. 
. order FTIMM3 ft_immig_2020Sep ft_white_2020Sep ft_black_2020Sep ft_latino_2020Sep ft_asian_2020Sep

. 
. *****************************************************************************************************************
> *
. * Control variables
. *****************************************************************************************************************
> *
. 
. codebook gender_2020Sep race_2020Sep birthyr_2020Sep educ_2020Sep marstat_2020Sep faminc_2020Sep religservice_202
> 0Sep pid7_2020Sep

-------------------------------------------------------------------------------------------------------------------
gender_2020Sep                                                                                               Gender
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: gender_2020Sep

                 Range: [1,2]                         Units: 1
         Unique values: 2                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        2,866         1  Male
                        3,034         2  Female
                        6,617         .  

-------------------------------------------------------------------------------------------------------------------
race_2020Sep                                                                                         Race/ethnicity
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: race_2020Sep

                 Range: [1,8]                         Units: 1
         Unique values: 8                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        4,059         1  White
                          664         2  Black
                          706         3  Hispanic
                          191         4  Asian
                           46         5  Native American
                           99         6  Two or more races
                          129         7  Other
                            6         8  Middle Eastern
                        6,617         .  

-------------------------------------------------------------------------------------------------------------------
birthyr_2020Sep                                                                                          Birth year
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (int)

                 Range: [1925,2002]                   Units: 1
         Unique values: 77                        Missing .: 6,617/12,517

                  Mean: 1969.06
             Std. dev.: 17.3627

           Percentiles:     10%       25%       50%       75%       90%
                           1948      1956      1966      1983      1995

-------------------------------------------------------------------------------------------------------------------
educ_2020Sep                                                                   Highest level of education completed
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: educ_2020Sep

                 Range: [1,6]                         Units: 1
         Unique values: 6                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                          164         1  No HS
                        1,551         2  High school graduate
                        1,457         3  Some college
                          670         4  2-year
                        1,291         5  4-year
                          767         6  Post-grad
                        6,617         .  

-------------------------------------------------------------------------------------------------------------------
marstat_2020Sep                                                                                      Marital status
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: marstat_2020Sep

                 Range: [1,6]                         Units: 1
         Unique values: 6                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        2,863         1  Married
                           90         2  Separated
                          613         3  Divorced
                          341         4  Widowed
                        1,729         5  Never married
                          264         6  Domestic / civil partnership
                        6,617         .  

-------------------------------------------------------------------------------------------------------------------
faminc_2020Sep                                                                 Family's annual income of respondent
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: faminc_new_2020Sep

                 Range: [1,97]                        Units: 1
         Unique values: 17                        Missing .: 6,617/12,517

              Examples: 6     $50,000 - $59,999
                        13    $200,000 - $249,999
                        .     
                        .     

-------------------------------------------------------------------------------------------------------------------
religservice_2020Sep                                                                   Religious service attendance
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: pew_churatd_2020Sep

                 Range: [1,98]                        Units: 1
         Unique values: 8                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                          364         1  More than once a week
                        1,001         2  Once a week
                          342         3  Once or twice a month
                          713         4  A few times a year
                        1,260         5  Seldom
                        2,082         6  Never
                          137         7  Don't know
                            1        98  skipped
                        6,617         .  

-------------------------------------------------------------------------------------------------------------------
pid7_2020Sep                                                                                      Party ID, 7-point
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: pid7_2020Sep

                 Range: [1,8]                         Units: 1
         Unique values: 8                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        1,581         1  Strong Democrat
                          689         2  Not very strong Democrat
                          634         3  Lean Democrat
                          910         4  Independent
                          478         5  Lean Republican
                          520         6  Not very strong Republican
                          939         7  Strong Republican
                          149         8  Not sure
                        6,617         .  

. 
. tab      gender_2020Sep

     Gender |      Freq.     Percent        Cum.
------------+-----------------------------------
       Male |      2,866       48.58       48.58
     Female |      3,034       51.42      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. clonevar GENDER = gender_2020Sep
(6,617 missing values generated)

. 
. codebook race_2020Sep

-------------------------------------------------------------------------------------------------------------------
race_2020Sep                                                                                         Race/ethnicity
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: race_2020Sep

                 Range: [1,8]                         Units: 1
         Unique values: 8                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        4,059         1  White
                          664         2  Black
                          706         3  Hispanic
                          191         4  Asian
                           46         5  Native American
                           99         6  Two or more races
                          129         7  Other
                            6         8  Middle Eastern
                        6,617         .  

. recode   race_2020Sep (1=1 "White") (2=2 "Black") (3=3 "Hispanic") (4=4 "Asian") (5/8=5 "Other"), gen(RACE)
(234 differences between race_2020Sep and RACE)

. tab      race_2020Sep RACE

                  |        RECODE of race_2020Sep (Race/ethnicity)
   Race/ethnicity |     White      Black   Hispanic      Asian      Other |     Total
------------------+-------------------------------------------------------+----------
            White |     4,059          0          0          0          0 |     4,059 
            Black |         0        664          0          0          0 |       664 
         Hispanic |         0          0        706          0          0 |       706 
            Asian |         0          0          0        191          0 |       191 
  Native American |         0          0          0          0         46 |        46 
Two or more races |         0          0          0          0         99 |        99 
            Other |         0          0          0          0        129 |       129 
   Middle Eastern |         0          0          0          0          6 |         6 
------------------+-------------------------------------------------------+----------
            Total |     4,059        664        706        191        280 |     5,900 

. 
. recode   RACE (1=0) (2/5=1), gen(RACENW)
(5,900 differences between RACE and RACENW)

. tab      race_2020Sep RACENW

                  |    RECODE of RACE
                  |      (RECODE of
                  |     race_2020Sep
                  |   (Race/ethnicity))
   Race/ethnicity |         0          1 |     Total
------------------+----------------------+----------
            White |     4,059          0 |     4,059 
            Black |         0        664 |       664 
         Hispanic |         0        706 |       706 
            Asian |         0        191 |       191 
  Native American |         0         46 |        46 
Two or more races |         0         99 |        99 
            Other |         0        129 |       129 
   Middle Eastern |         0          6 |         6 
------------------+----------------------+----------
            Total |     4,059      1,841 |     5,900 

. 
. sum      birthyr_2020Sep

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
birthyr_20~p |      5,900    1969.058    17.36274       1925       2002

. gen      AGE = 2020 - birthyr_2020Sep
(6,617 missing values generated)

. tab      AGE

        AGE |      Freq.     Percent        Cum.
------------+-----------------------------------
         18 |         22        0.37        0.37
         19 |         34        0.58        0.95
         20 |        114        1.93        2.88
         21 |         94        1.59        4.47
         22 |         87        1.47        5.95
         23 |         88        1.49        7.44
         24 |         70        1.19        8.63
         25 |         93        1.58       10.20
         26 |         74        1.25       11.46
         27 |         93        1.58       13.03
         28 |        104        1.76       14.80
         29 |         94        1.59       16.39
         30 |         89        1.51       17.90
         31 |         63        1.07       18.97
         32 |         67        1.14       20.10
         33 |         48        0.81       20.92
         34 |         76        1.29       22.20
         35 |         83        1.41       23.61
         36 |         80        1.36       24.97
         37 |         80        1.36       26.32
         38 |         91        1.54       27.86
         39 |         90        1.53       29.39
         40 |        102        1.73       31.12
         41 |         72        1.22       32.34
         42 |         80        1.36       33.69
         43 |         97        1.64       35.34
         44 |         92        1.56       36.90
         45 |         61        1.03       37.93
         46 |         58        0.98       38.92
         47 |         54        0.92       39.83
         48 |         60        1.02       40.85
         49 |         78        1.32       42.17
         50 |        100        1.69       43.86
         51 |         98        1.66       45.53
         52 |         91        1.54       47.07
         53 |         86        1.46       48.53
         54 |        120        2.03       50.56
         55 |        128        2.17       52.73
         56 |        154        2.61       55.34
         57 |        136        2.31       57.64
         58 |        148        2.51       60.15
         59 |        165        2.80       62.95
         60 |        163        2.76       65.71
         61 |        153        2.59       68.31
         62 |        147        2.49       70.80
         63 |        174        2.95       73.75
         64 |        171        2.90       76.64
         65 |        142        2.41       79.05
         66 |        139        2.36       81.41
         67 |        131        2.22       83.63
         68 |         89        1.51       85.14
         69 |         89        1.51       86.64
         70 |        103        1.75       88.39
         71 |         87        1.47       89.86
         72 |         66        1.12       90.98
         73 |         58        0.98       91.97
         74 |         48        0.81       92.78
         75 |         39        0.66       93.44
         76 |         41        0.69       94.14
         77 |         45        0.76       94.90
         78 |         35        0.59       95.49
         79 |         36        0.61       96.10
         80 |         29        0.49       96.59
         81 |         40        0.68       97.27
         82 |         28        0.47       97.75
         83 |         27        0.46       98.20
         84 |         23        0.39       98.59
         85 |         15        0.25       98.85
         86 |         13        0.22       99.07
         87 |         14        0.24       99.31
         88 |         14        0.24       99.54
         89 |         10        0.17       99.71
         90 |          6        0.10       99.81
         91 |          4        0.07       99.88
         92 |          2        0.03       99.92
         93 |          3        0.05       99.97
         95 |          2        0.03      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. recode   AGE (18/30 = 1 "Age 18/30") (31/45 = 2 "Age 31/45") (46/60 = 3 "Age 46/60") (61/99 = 4 "Age 61+"), gen(A
> GEGRP)
(5,900 differences between AGE and AGEGRP)

. tab      AGEGRP

  RECODE of |
        AGE |      Freq.     Percent        Cum.
------------+-----------------------------------
  Age 18/30 |      1,056       17.90       17.90
  Age 31/45 |      1,182       20.03       37.93
  Age 46/60 |      1,639       27.78       65.71
    Age 61+ |      2,023       34.29      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. tab      AGEGRP

  RECODE of |
        AGE |      Freq.     Percent        Cum.
------------+-----------------------------------
  Age 18/30 |      1,056       17.90       17.90
  Age 31/45 |      1,182       20.03       37.93
  Age 46/60 |      1,639       27.78       65.71
    Age 61+ |      2,023       34.29      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. clonevar EDUC = educ_2020Sep
(6,617 missing values generated)

. tab      educ_2020Sep EDUC

    Highest level of |               Highest level of education completed
 education completed |     No HS  High scho  Some coll     2-year     4-year  Post-grad |     Total
---------------------+------------------------------------------------------------------+----------
               No HS |       164          0          0          0          0          0 |       164 
High school graduate |         0      1,551          0          0          0          0 |     1,551 
        Some college |         0          0      1,457          0          0          0 |     1,457 
              2-year |         0          0          0        670          0          0 |       670 
              4-year |         0          0          0          0      1,291          0 |     1,291 
           Post-grad |         0          0          0          0          0        767 |       767 
---------------------+------------------------------------------------------------------+----------
               Total |       164      1,551      1,457        670      1,291        767 |     5,900 

. 
. codebook marstat_2020Sep

-------------------------------------------------------------------------------------------------------------------
marstat_2020Sep                                                                                      Marital status
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: marstat_2020Sep

                 Range: [1,6]                         Units: 1
         Unique values: 6                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        2,863         1  Married
                           90         2  Separated
                          613         3  Divorced
                          341         4  Widowed
                        1,729         5  Never married
                          264         6  Domestic / civil partnership
                        6,617         .  

. recode   marstat_2020Sep (1=1 "Married") (2/3=2 "Separated / Divorced") (4=4 "Widowed") (5=5 "Never married") (6=
> 6 "Domestic/civil partnership"), gen(MARITAL)
(613 differences between marstat_2020Sep and MARITAL)

. tab      marstat_2020Sep MARITAL

                      |       RECODE of marstat_2020Sep (Marital status)
       Marital status |   Married  Separated    Widowed  Never mar  Domestic/ |     Total
----------------------+-------------------------------------------------------+----------
              Married |     2,863          0          0          0          0 |     2,863 
            Separated |         0         90          0          0          0 |        90 
             Divorced |         0        613          0          0          0 |       613 
              Widowed |         0          0        341          0          0 |       341 
        Never married |         0          0          0      1,729          0 |     1,729 
Domestic / civil part |         0          0          0          0        264 |       264 
----------------------+-------------------------------------------------------+----------
                Total |     2,863        703        341      1,729        264 |     5,900 

. 
. tab      faminc_2020Sep

    Family's annual |
          income of |
         respondent |      Freq.     Percent        Cum.
--------------------+-----------------------------------
  Less than $10,000 |        274        4.64        4.64
  $10,000 - $19,999 |        427        7.24       11.88
  $20,000 - $29,999 |        482        8.17       20.05
  $30,000 - $39,999 |        534        9.05       29.10
  $40,000 - $49,999 |        456        7.73       36.83
  $50,000 - $59,999 |        465        7.88       44.71
  $60,000 - $69,999 |        398        6.75       51.46
  $70,000 - $79,999 |        434        7.36       58.81
  $80,000 - $99,999 |        459        7.78       66.59
$100,000 - $119,999 |        365        6.19       72.78
$120,000 - $149,999 |        348        5.90       78.68
$150,000 - $199,999 |        274        4.64       83.32
$200,000 - $249,999 |        118        2.00       85.32
$250,000 - $349,999 |         50        0.85       86.17
$350,000 - $499,999 |         23        0.39       86.56
   $500,000 or more |         21        0.36       86.92
  Prefer not to say |        772       13.08      100.00
--------------------+-----------------------------------
              Total |      5,900      100.00

. tab      faminc_2020Sep, nol

   Family's |
     annual |
  income of |
 respondent |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        274        4.64        4.64
          2 |        427        7.24       11.88
          3 |        482        8.17       20.05
          4 |        534        9.05       29.10
          5 |        456        7.73       36.83
          6 |        465        7.88       44.71
          7 |        398        6.75       51.46
          8 |        434        7.36       58.81
          9 |        459        7.78       66.59
         10 |        365        6.19       72.78
         11 |        348        5.90       78.68
         12 |        274        4.64       83.32
         13 |        118        2.00       85.32
         14 |         50        0.85       86.17
         15 |         23        0.39       86.56
         16 |         21        0.36       86.92
         97 |        772       13.08      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. recode   faminc_2020Sep (1/3 = 1 "Less than $30k") (4/7 = 2 "$30k-$69k") (8/9 = 3 "$70k-$99k") (10/11 = 4 "$100k-
> $149k") (12/16 = 5 "$150k +") (97=97 "Prefer to not say"), gen(HHINCOME)
(4,854 differences between faminc_2020Sep and HHINCOME)

. tab      faminc_2020Sep HHINCOME

    Family's annual |
          income of |  RECODE of faminc_2020Sep (Family's annual income of respondent)
         respondent | Less than  $30k-$69k  $70k-$99k  $100k-$14    $150k +  Prefer to |     Total
--------------------+------------------------------------------------------------------+----------
  Less than $10,000 |       274          0          0          0          0          0 |       274 
  $10,000 - $19,999 |       427          0          0          0          0          0 |       427 
  $20,000 - $29,999 |       482          0          0          0          0          0 |       482 
  $30,000 - $39,999 |         0        534          0          0          0          0 |       534 
  $40,000 - $49,999 |         0        456          0          0          0          0 |       456 
  $50,000 - $59,999 |         0        465          0          0          0          0 |       465 
  $60,000 - $69,999 |         0        398          0          0          0          0 |       398 
  $70,000 - $79,999 |         0          0        434          0          0          0 |       434 
  $80,000 - $99,999 |         0          0        459          0          0          0 |       459 
$100,000 - $119,999 |         0          0          0        365          0          0 |       365 
$120,000 - $149,999 |         0          0          0        348          0          0 |       348 
$150,000 - $199,999 |         0          0          0          0        274          0 |       274 
$200,000 - $249,999 |         0          0          0          0        118          0 |       118 
$250,000 - $349,999 |         0          0          0          0         50          0 |        50 
$350,000 - $499,999 |         0          0          0          0         23          0 |        23 
   $500,000 or more |         0          0          0          0         21          0 |        21 
  Prefer not to say |         0          0          0          0          0        772 |       772 
--------------------+------------------------------------------------------------------+----------
              Total |     1,183      1,853        893        713        486        772 |     5,900 

. 
. codebook religservice_2020Sep 

-------------------------------------------------------------------------------------------------------------------
religservice_2020Sep                                                                   Religious service attendance
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: pew_churatd_2020Sep

                 Range: [1,98]                        Units: 1
         Unique values: 8                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                          364         1  More than once a week
                        1,001         2  Once a week
                          342         3  Once or twice a month
                          713         4  A few times a year
                        1,260         5  Seldom
                        2,082         6  Never
                          137         7  Don't know
                            1        98  skipped
                        6,617         .  

. recode   religservice_2020Sep (1/2=1 "More than once a week / Once a week") (3/4=2 "Once or twice a month / A few
>  times a year") (5=3 "Seldom") (6=4 "Never") (7 98=5 "Don't know / Skipped"), gen(ATTEND)
(5,536 differences between religservice_2020Sep and ATTEND)

. tab      religservice_2020Sep ATTEND

                      |   RECODE of religservice_2020Sep (Religious service
    Religious service |                      attendance)
           attendance | More than  Once or t     Seldom      Never  Don't kno |     Total
----------------------+-------------------------------------------------------+----------
More than once a week |       364          0          0          0          0 |       364 
          Once a week |     1,001          0          0          0          0 |     1,001 
Once or twice a month |         0        342          0          0          0 |       342 
   A few times a year |         0        713          0          0          0 |       713 
               Seldom |         0          0      1,260          0          0 |     1,260 
                Never |         0          0          0      2,082          0 |     2,082 
           Don't know |         0          0          0          0        137 |       137 
              skipped |         0          0          0          0          1 |         1 
----------------------+-------------------------------------------------------+----------
                Total |     1,365      1,055      1,260      2,082        138 |     5,900 

. 
. tab      pid7_2020Sep

         Party ID, 7-point |      Freq.     Percent        Cum.
---------------------------+-----------------------------------
           Strong Democrat |      1,581       26.80       26.80
  Not very strong Democrat |        689       11.68       38.47
             Lean Democrat |        634       10.75       49.22
               Independent |        910       15.42       64.64
           Lean Republican |        478        8.10       72.75
Not very strong Republican |        520        8.81       81.56
         Strong Republican |        939       15.92       97.47
                  Not sure |        149        2.53      100.00
---------------------------+-----------------------------------
                     Total |      5,900      100.00

. clonevar PID7 = pid7_2020Sep
(6,617 missing values generated)

. tab      pid7_2020Sep PID7

                      |                              Party ID, 7-point
    Party ID, 7-point | Strong De  Not very   Lean Demo  Independe  Lean Repu  Not very   Strong Re |     Total
----------------------+-----------------------------------------------------------------------------+----------
      Strong Democrat |     1,581          0          0          0          0          0          0 |     1,581 
Not very strong Democ |         0        689          0          0          0          0          0 |       689 
        Lean Democrat |         0          0        634          0          0          0          0 |       634 
          Independent |         0          0          0        910          0          0          0 |       910 
      Lean Republican |         0          0          0          0        478          0          0 |       478 
Not very strong Repub |         0          0          0          0          0        520          0 |       520 
    Strong Republican |         0          0          0          0          0          0        939 |       939 
             Not sure |         0          0          0          0          0          0          0 |       149 
----------------------+-----------------------------------------------------------------------------+----------
                Total |     1,581        689        634        910        478        520        939 |     5,900 


                      | Party ID,
                      |  7-point
    Party ID, 7-point |  Not sure |     Total
----------------------+-----------+----------
      Strong Democrat |         0 |     1,581 
Not very strong Democ |         0 |       689 
        Lean Democrat |         0 |       634 
          Independent |         0 |       910 
      Lean Republican |         0 |       478 
Not very strong Repub |         0 |       520 
    Strong Republican |         0 |       939 
             Not sure |       149 |       149 
----------------------+-----------+----------
                Total |       149 |     5,900 

. 
. clonevar PID3 = pid3_2020Sep
(6,617 missing values generated)

. codebook pid3_2020Sep

-------------------------------------------------------------------------------------------------------------------
pid3_2020Sep                                                                                      Party ID, 3-point
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: pid3_2020Sep

                 Range: [1,5]                         Units: 1
         Unique values: 5                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        2,270         1  Democrat
                        1,459         2  Republican
                        1,807         3  Independent
                          142         4  Other
                          222         5  Not sure
                        6,617         .  

. recode   PID3 (5=4)
(222 changes made to PID3)

. tab      pid3_2020Sep PID3

  Party ID, |              Party ID, 3-point
    3-point |  Democrat  Republica  Independe      Other |     Total
------------+--------------------------------------------+----------
   Democrat |     2,270          0          0          0 |     2,270 
 Republican |         0      1,459          0          0 |     1,459 
Independent |         0          0      1,807          0 |     1,807 
      Other |         0          0          0        142 |       142 
   Not sure |         0          0          0        222 |       222 
------------+--------------------------------------------+----------
      Total |     2,270      1,459      1,807        364 |     5,900 

. 
. clonevar STATE = inputstate_2020Sep 
(6,617 missing values generated)

. 
. recode ft_blm_2020Sep    (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTBLM5)
(5,346 differences between ft_blm_2020Sep and FTBLM5)

. recode ft_gay_2020Sep    (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTGAY5)
(5,774 differences between ft_gay_2020Sep and FTGAY5)

. recode ft_muslim_2020Sep (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTMUSLM5)
(5,735 differences between ft_muslim_2020Sep and FTMUSLM5)

. recode ft_police_2020Sep (0/25=0) (26/49=1) (50=2) (51/75=4) (76/99=5) (100=6) (min/-1 101/max=3), gen(FTPOLICE5)
(5,792 differences between ft_police_2020Sep and FTPOLICE5)

. label  values FTBLM5 FTGAY5 FTMUSLM5 FTPOLICE5 FT5

. tab1          FTBLM5 FTGAY5 FTMUSLM5 FTPOLICE5 

-> tabulation of FTBLM5  

  RECODE of |
ft_blm_2020 |
        Sep |
   (Feeling |
thermometer |
  for Black |
      Lives |
    Matter) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |      2,025       34.32       34.32
      26/49 |        463        7.85       42.17
         50 |        209        3.54       45.71
    Missing |        195        3.31       49.02
      51/75 |        946       16.03       65.05
      76/99 |      1,543       26.15       91.20
        100 |        519        8.80      100.00
------------+-----------------------------------
      Total |      5,900      100.00

-> tabulation of FTGAY5  

  RECODE of |
ft_gay_2020 |
        Sep |
   (Feeling |
thermometer |
for gay and |
    lesbian |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        740       12.54       12.54
      26/49 |        553        9.37       21.92
         50 |        556        9.42       31.34
    Missing |        234        3.97       35.31
      51/75 |      1,267       21.47       56.78
      76/99 |      1,944       32.95       89.73
        100 |        606       10.27      100.00
------------+-----------------------------------
      Total |      5,900      100.00

-> tabulation of FTMUSLM5  

  RECODE of |
ft_muslim_2 |
     020Sep |
   (Feeling |
thermometer |
 for Muslim |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        931       15.78       15.78
      26/49 |        805       13.64       29.42
         50 |        580        9.83       39.25
    Missing |        371        6.29       45.54
      51/75 |      1,443       24.46       70.00
      76/99 |      1,445       24.49       94.49
        100 |        325        5.51      100.00
------------+-----------------------------------
      Total |      5,900      100.00

-> tabulation of FTPOLICE5  

  RECODE of |
ft_police_2 |
     020Sep |
   (Feeling |
thermometer |
 for police |
  officers) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        747       12.66       12.66
      26/49 |        776       13.15       25.81
         50 |        251        4.25       30.07
    Missing |        139        2.36       32.42
      51/75 |      1,252       21.22       53.64
      76/99 |      2,170       36.78       90.42
        100 |        565        9.58      100.00
------------+-----------------------------------
      Total |      5,900      100.00

. 
. tab1 VOTEBT FTIMMIG5 FTIMM3 GENDER RACE AGEGRP EDUC MARITAL HHINCOME ATTEND PID7 STATE FTWHITE5 FTBLACK5 FTHISPN5
>  FTASIAN5 FTBLM5 FTGAY5 FTMUSLM5 FTPOLICE5 if weight_genpop_2020Nov != . & VOTEBT !=.

-> tabulation of VOTEBT if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
presvote_20 |
20Nov (2020 |
Presidentia |
    l vote, |
post-electi |
        on) |      Freq.     Percent        Cum.
------------+-----------------------------------
      Trump |      1,743       39.87       39.87
      Biden |      2,629       60.13      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTIMMIG5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_immig_20 |
      20Sep |
   (Feeling |
thermometer |
        for |
immigrants) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        317        7.25        7.25
      26/49 |        399        9.13       16.38
         50 |        366        8.37       24.75
    Missing |        132        3.02       27.77
      51/75 |      1,167       26.69       54.46
      76/99 |      1,640       37.51       91.97
        100 |        351        8.03      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTIMM3 if weight_genpop_2020Nov != . & VOTEBT !=. 

                   FTIMM3 |      Freq.     Percent        Cum.
--------------------------+-----------------------------------
       Cold to immigrants |        404        9.24        9.24
Indifferent to immigrants |        270        6.18       15.42
       Warm to immigrants |        460       10.52       25.94
                  Missing |        227        5.19       31.13
                 Residual |      3,011       68.87      100.00
--------------------------+-----------------------------------
                    Total |      4,372      100.00

-> tabulation of GENDER if weight_genpop_2020Nov != . & VOTEBT !=. 

     Gender |      Freq.     Percent        Cum.
------------+-----------------------------------
       Male |      2,130       48.72       48.72
     Female |      2,242       51.28      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of RACE if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
race_2020Se |
          p |
(Race/ethni |
      city) |      Freq.     Percent        Cum.
------------+-----------------------------------
      White |      3,189       72.94       72.94
      Black |        455       10.41       83.35
   Hispanic |        424        9.70       93.05
      Asian |        116        2.65       95.70
      Other |        188        4.30      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of AGEGRP if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
        AGE |      Freq.     Percent        Cum.
------------+-----------------------------------
  Age 18/30 |        520       11.89       11.89
  Age 31/45 |        790       18.07       29.96
  Age 46/60 |      1,343       30.72       60.68
    Age 61+ |      1,719       39.32      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of EDUC if weight_genpop_2020Nov != . & VOTEBT !=. 

    Highest level of |
 education completed |      Freq.     Percent        Cum.
---------------------+-----------------------------------
               No HS |         80        1.83        1.83
High school graduate |      1,090       24.93       26.76
        Some college |      1,032       23.60       50.37
              2-year |        488       11.16       61.53
              4-year |      1,038       23.74       85.27
           Post-grad |        644       14.73      100.00
---------------------+-----------------------------------
               Total |      4,372      100.00

-> tabulation of MARITAL if weight_genpop_2020Nov != . & VOTEBT !=. 

 RECODE of marstat_2020Sep |
          (Marital status) |      Freq.     Percent        Cum.
---------------------------+-----------------------------------
                   Married |      2,278       52.10       52.10
      Separated / Divorced |        523       11.96       64.07
                   Widowed |        270        6.18       70.24
             Never married |      1,115       25.50       95.75
Domestic/civil partnership |        186        4.25      100.00
---------------------------+-----------------------------------
                     Total |      4,372      100.00

-> tabulation of HHINCOME if weight_genpop_2020Nov != . & VOTEBT !=. 

        RECODE of |
   faminc_2020Sep |
 (Family's annual |
        income of |
      respondent) |      Freq.     Percent        Cum.
------------------+-----------------------------------
   Less than $30k |        753       17.22       17.22
        $30k-$69k |      1,389       31.77       48.99
        $70k-$99k |        715       16.35       65.35
      $100k-$149k |        563       12.88       78.23
          $150k + |        403        9.22       87.44
Prefer to not say |        549       12.56      100.00
------------------+-----------------------------------
            Total |      4,372      100.00

-> tabulation of ATTEND if weight_genpop_2020Nov != . & VOTEBT !=. 

         RECODE of religservice_2020Sep |
         (Religious service attendance) |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
    More than once a week / Once a week |      1,033       23.63       23.63
Once or twice a month / A few times a y |        763       17.45       41.08
                                 Seldom |        959       21.94       63.01
                                  Never |      1,539       35.20       98.22
                   Don't know / Skipped |         78        1.78      100.00
----------------------------------------+-----------------------------------
                                  Total |      4,372      100.00

-> tabulation of PID7 if weight_genpop_2020Nov != . & VOTEBT !=. 

         Party ID, 7-point |      Freq.     Percent        Cum.
---------------------------+-----------------------------------
           Strong Democrat |      1,303       29.80       29.80
  Not very strong Democrat |        527       12.05       41.86
             Lean Democrat |        475       10.86       52.72
               Independent |        524       11.99       64.71
           Lean Republican |        365        8.35       73.06
Not very strong Republican |        392        8.97       82.02
         Strong Republican |        750       17.15       99.18
                  Not sure |         36        0.82      100.00
---------------------------+-----------------------------------
                     Total |      4,372      100.00

-> tabulation of STATE if weight_genpop_2020Nov != . & VOTEBT !=. 

            State of residence |      Freq.     Percent        Cum.
-------------------------------+-----------------------------------
                       Alabama |         51        1.17        1.17
                        Alaska |         16        0.37        1.53
                       Arizona |        101        2.31        3.84
                      Arkansas |         36        0.82        4.67
                    California |        449       10.27       14.94
                      Colorado |         81        1.85       16.79
                   Connecticut |         40        0.91       17.70
                      Delaware |         14        0.32       18.02
          District of Columbia |         14        0.32       18.34
                       Florida |        327        7.48       25.82
                       Georgia |        142        3.25       29.07
                        Hawaii |         15        0.34       29.41
                         Idaho |         37        0.85       30.26
                      Illinois |        178        4.07       34.33
                       Indiana |         92        2.10       36.44
                          Iowa |         62        1.42       37.85
                        Kansas |         38        0.87       38.72
                      Kentucky |         54        1.24       39.96
                     Louisiana |         38        0.87       40.83
                         Maine |         26        0.59       41.42
                      Maryland |         88        2.01       43.44
                 Massachusetts |         93        2.13       45.56
                      Michigan |        148        3.39       48.95
                     Minnesota |         72        1.65       50.59
                   Mississippi |         27        0.62       51.21
                      Missouri |         89        2.04       53.25
                       Montana |         21        0.48       53.73
                      Nebraska |         23        0.53       54.25
                        Nevada |         47        1.08       55.33
                 New Hampshire |         24        0.55       55.88
                    New Jersey |        126        2.88       58.76
                    New Mexico |         37        0.85       59.61
                      New York |        240        5.49       65.10
                North Carolina |        106        2.42       67.52
                  North Dakota |          4        0.09       67.61
                          Ohio |        158        3.61       71.23
                      Oklahoma |         29        0.66       71.89
                        Oregon |         65        1.49       73.38
                  Pennsylvania |        251        5.74       79.12
                  Rhode Island |         13        0.30       79.41
                South Carolina |         53        1.21       80.63
                  South Dakota |         19        0.43       81.06
                     Tennessee |         88        2.01       83.07
                         Texas |        271        6.20       89.27
                          Utah |         43        0.98       90.26
                       Vermont |         15        0.34       90.60
                      Virginia |        127        2.90       93.50
                    Washington |        118        2.70       96.20
                 West Virginia |         33        0.75       96.96
                     Wisconsin |        122        2.79       99.75
                       Wyoming |         11        0.25      100.00
-------------------------------+-----------------------------------
                         Total |      4,372      100.00

-> tabulation of FTWHITE5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_white_20 |
      20Sep |
   (Feeling |
thermometer |
  for white |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        188        4.30        4.30
      26/49 |        411        9.40       13.70
         50 |        449       10.27       23.97
    Missing |         79        1.81       25.78
      51/75 |      1,119       25.59       51.37
      76/99 |      1,779       40.69       92.06
        100 |        347        7.94      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTBLACK5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_black_20 |
      20Sep |
   (Feeling |
thermometer |
  for Black |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        217        4.96        4.96
      26/49 |        306        7.00       11.96
         50 |        338        7.73       19.69
    Missing |         81        1.85       21.55
      51/75 |      1,051       24.04       45.59
      76/99 |      1,868       42.73       88.31
        100 |        511       11.69      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTHISPN5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_latino_2 |
     020Sep |
   (Feeling |
thermometer |
 for Latino |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        160        3.66        3.66
      26/49 |        283        6.47       10.13
         50 |        350        8.01       18.14
    Missing |        121        2.77       20.91
      51/75 |      1,136       25.98       46.89
      76/99 |      1,862       42.59       89.48
        100 |        460       10.52      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTASIAN5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_asian_20 |
      20Sep |
   (Feeling |
thermometer |
  for Asian |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        134        3.06        3.06
      26/49 |        238        5.44        8.51
         50 |        386        8.83       17.34
    Missing |        154        3.52       20.86
      51/75 |      1,063       24.31       45.17
      76/99 |      1,951       44.62       89.80
        100 |        446       10.20      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTBLM5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_blm_2020 |
        Sep |
   (Feeling |
thermometer |
  for Black |
      Lives |
    Matter) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |      1,574       36.00       36.00
      26/49 |        313        7.16       43.16
         50 |        136        3.11       46.27
    Missing |         83        1.90       48.17
      51/75 |        692       15.83       64.00
      76/99 |      1,195       27.33       91.33
        100 |        379        8.67      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTGAY5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_gay_2020 |
        Sep |
   (Feeling |
thermometer |
for gay and |
    lesbian |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        539       12.33       12.33
      26/49 |        394        9.01       21.34
         50 |        396        9.06       30.40
    Missing |        118        2.70       33.10
      51/75 |        952       21.77       54.87
      76/99 |      1,525       34.88       89.75
        100 |        448       10.25      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTMUSLM5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_muslim_2 |
     020Sep |
   (Feeling |
thermometer |
 for Muslim |
    people) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        735       16.81       16.81
      26/49 |        571       13.06       29.87
         50 |        405        9.26       39.14
    Missing |        209        4.78       43.92
      51/75 |      1,103       25.23       69.14
      76/99 |      1,113       25.46       94.60
        100 |        236        5.40      100.00
------------+-----------------------------------
      Total |      4,372      100.00

-> tabulation of FTPOLICE5 if weight_genpop_2020Nov != . & VOTEBT !=. 

  RECODE of |
ft_police_2 |
     020Sep |
   (Feeling |
thermometer |
 for police |
  officers) |      Freq.     Percent        Cum.
------------+-----------------------------------
       0/25 |        502       11.48       11.48
      26/49 |        537       12.28       23.76
         50 |        180        4.12       27.88
    Missing |         53        1.21       29.09
      51/75 |        924       21.13       50.23
      76/99 |      1,730       39.57       89.80
        100 |        446       10.20      100.00
------------+-----------------------------------
      Total |      4,372      100.00

. 
. *****************************************************************************************************************
> *
. * Figure 1. Distribution for FTs [using Sept 2020 weights]
. *****************************************************************************************************************
> *
. 
. svyset [pw = weight_genpop_2020Sep]

Sampling weights: weight_genpop_2020Sep
             VCE: linearized
     Single unit: missing
        Strata 1: <one>
 Sampling unit 1: <observations>
           FPC 1: <zero>

. 
. sum weight_genpop_2020Nov if FTIMMIG!=. & FTWHITE!=. & FTBLACK!=. & FTHISPN!=. & FTASIAN!=.

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
we~p_2020Nov |      4,616    .9818512    .6915172   .1320332   7.020961

. 
. svy: mean FTIMMIG FTWHITE FTBLACK FTHISPN FTASIAN, level(83.4)
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =     1          Number of obs   =      5,485
Number of PSUs   = 5,485          Population size = 5,403.9605
                                  Design df       =      5,484

--------------------------------------------------------------
             |             Linearized
             |       Mean   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
     FTIMMIG |   66.55914   .4129753      65.98702    67.13126
     FTWHITE |   68.22132   .3869412      67.68527    68.75737
     FTBLACK |   71.46689   .3984118      70.91495    72.01883
     FTHISPN |    72.3389   .3689914      71.82772    72.85009
     FTASIAN |   72.12419   .3790756      71.59903    72.64934
--------------------------------------------------------------

. svy: mean FTIMMIG, level(83.4)
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =     1          Number of obs   =      5,633
Number of PSUs   = 5,633          Population size = 5,571.7845
                                  Design df       =      5,632

--------------------------------------------------------------
             |             Linearized
             |       Mean   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
     FTIMMIG |   66.23725   .4101912      65.66899    66.80551
--------------------------------------------------------------

. svy: mean FTWHITE, level(83.4)
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =     1          Number of obs   =      5,721
Number of PSUs   = 5,721          Population size = 5,669.9027
                                  Design df       =      5,720

--------------------------------------------------------------
             |             Linearized
             |       Mean   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
     FTWHITE |   68.21064   .3821925      67.68117    68.74011
--------------------------------------------------------------

. svy: mean FTBLACK, level(83.4)
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =     1          Number of obs   =      5,718
Number of PSUs   = 5,718          Population size = 5,673.8335
                                  Design df       =      5,717

--------------------------------------------------------------
             |             Linearized
             |       Mean   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
     FTBLACK |    71.5292    .392228      70.98583    72.07257
--------------------------------------------------------------

. svy: mean FTHISPN, level(83.4)
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =     1          Number of obs   =      5,652
Number of PSUs   = 5,652          Population size = 5,596.9203
                                  Design df       =      5,651

--------------------------------------------------------------
             |             Linearized
             |       Mean   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
     FTHISPN |   72.18267   .3661338      71.67544    72.68989
--------------------------------------------------------------

. svy: mean FTASIAN, level(83.4)
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =     1          Number of obs   =      5,613
Number of PSUs   = 5,613          Population size = 5,549.5539
                                  Design df       =      5,612

--------------------------------------------------------------
             |             Linearized
             |       Mean   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
     FTASIAN |   71.98124   .3784792      71.45691    72.50556
--------------------------------------------------------------

. 
. svy: prop FTIMMIG5, level(83.4)
(running proportion on estimation sample)

Survey: Proportion estimation

Number of strata =     1               Number of obs   = 5,900
Number of PSUs   = 5,900               Population size = 5,900
                                       Design df       = 5,899

--------------------------------------------------------------
             |             Linearized            Logit
             | Proportion   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
    FTIMMIG5 |
       0/25  |   .0841323   .0043261      .0783298    .0903225
      26/49  |    .103547   .0046567      .0972713    .1101782
         50  |   .0899263   .0041995      .0842756    .0959161
    Missing  |   .0556298   .0038384      .0505453    .0611927
      51/75  |   .2576972   .0064052       .248924    .2666698
      76/99  |   .3314564   .0067876      .3221214    .3409259
        100  |    .077611   .0040044      .0722419    .0833432
--------------------------------------------------------------

. svy: prop FTWHITE5, level(83.4)
(running proportion on estimation sample)

Survey: Proportion estimation

Number of strata =     1               Number of obs   = 5,900
Number of PSUs   = 5,900               Population size = 5,900
                                       Design df       = 5,899

--------------------------------------------------------------
             |             Linearized            Logit
             | Proportion   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
    FTWHITE5 |
       0/25  |   .0550068   .0037137      .0500829    .0603839
      26/49  |   .1078019   .0048147       .101311    .1146556
         50  |   .1073693   .0046085      .1011499    .1139227
    Missing  |   .0389995   .0033283      .0346414    .0438811
      51/75  |   .2507287   .0064241      .2419346    .2597329
      76/99  |   .3612866   .0069032      .3517793    .3709038
        100  |   .0788072    .003958      .0734955    .0844677
--------------------------------------------------------------

. svy: prop FTBLACK5, level(83.4)
(running proportion on estimation sample)

Survey: Proportion estimation

Number of strata =     1               Number of obs   = 5,900
Number of PSUs   = 5,900               Population size = 5,900
                                       Design df       = 5,899

--------------------------------------------------------------
             |             Linearized            Logit
             | Proportion   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
    FTBLACK5 |
       0/25  |   .0562365    .003652       .051386     .061515
      26/49  |   .0807883   .0042104      .0751442    .0868165
         50  |   .0846467   .0040753      .0791692    .0904659
    Missing  |   .0383333   .0032013      .0341366     .043023
      51/75  |   .2385611   .0062873      .2299606      .24738
      76/99  |   .3862839   .0070989      .3764971    .3961635
        100  |   .1151502   .0047113      .1087826    .1218396
--------------------------------------------------------------

. svy: prop FTHISPN5, level(83.4)
(running proportion on estimation sample)

Survey: Proportion estimation

Number of strata =     1               Number of obs   = 5,900
Number of PSUs   = 5,900               Population size = 5,900
                                       Design df       = 5,899

--------------------------------------------------------------
             |             Linearized            Logit
             | Proportion   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
    FTHISPN5 |
       0/25  |   .0427693   .0030964      .0386793    .0472704
      26/49  |   .0754557   .0040312      .0700574    .0812336
         50  |    .085916   .0041187      .0803792    .0917961
    Missing  |   .0513694     .00369      .0464916    .0567287
      51/75  |   .2536452   .0064307      .2448402    .2626567
      76/99  |   .3841637   .0070887      .3743918      .39403
        100  |   .1066808   .0046025      .1004705    .1132266
--------------------------------------------------------------

. svy: prop FTASIAN5, level(83.4)
(running proportion on estimation sample)

Survey: Proportion estimation

Number of strata =     1               Number of obs   = 5,900
Number of PSUs   = 5,900               Population size = 5,900
                                       Design df       = 5,899

--------------------------------------------------------------
             |             Linearized            Logit
             | Proportion   std. err.   [83.4% conf. interval]
-------------+------------------------------------------------
    FTASIAN5 |
       0/25  |   .0403364   .0033243      .0359748    .0452021
      26/49  |   .0738372   .0041961      .0682307    .0798649
         50  |   .0902615   .0041703      .0846484    .0962078
    Missing  |   .0593976    .003912      .0542042    .0650544
      51/75  |   .2452713   .0064253      .2364795    .2542812
      76/99  |   .3912962   .0070547      .3815678    .4011117
        100  |   .0995997   .0043512       .093732    .1057919
--------------------------------------------------------------

. 
. *****************************************************************************************************************
> *
. * Figure 2. Subgroups [using Nov 2020 weights]
. *****************************************************************************************************************
> *
. 
. svyset [pw = weight_genpop_2020Nov]

Sampling weights: weight_genpop_2020Nov
             VCE: linearized
     Single unit: missing
        Strata 1: <one>
 Sampling unit 1: <observations>
           FPC 1: <zero>

. 
. * Full sample
. 
. svy                              : logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(32, 4340)     =      20.98
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -.9170523   .2405636    -3.81   0.000    -1.388679   -.4454257
                                     26/49  |  -.0110694   .2043357    -0.05   0.957    -.4116709    .3895321
                                   Missing  |   .3912078   .2967946     1.32   0.188    -.1906601    .9730756
                                     51/75  |   .8001307   .1670143     4.79   0.000     .4726981    1.127563
                                     76/99  |    1.55504   .1650634     9.42   0.000     1.231432    1.878647
                                       100  |    1.80116     .22614     7.96   0.000     1.357811    2.244509
                                            |
                                     GENDER |
                                    Female  |   .5869418    .084009     6.99   0.000     .4222416     .751642
                                            |
                                       RACE |
                                     Black  |   2.869364   .2275733    12.61   0.000     2.423205    3.315523
                                  Hispanic  |   1.056105   .1605429     6.58   0.000     .7413594     1.37085
                                     Asian  |   .7788077   .2740395     2.84   0.005     .2415513    1.316064
                                     Other  |   .1452118   .1886896     0.77   0.442    -.2247155    .5151391
                                            |
                                     AGEGRP |
                                 Age 31/45  |    -.44364   .1748288    -2.54   0.011    -.7863931   -.1008869
                                 Age 46/60  |  -.5464368   .1675532    -3.26   0.001    -.8749259   -.2179477
                                   Age 61+  |  -.4634302   .1698855    -2.73   0.006    -.7964919   -.1303686
                                            |
                                       EDUC |
                      High school graduate  |  -.6521282   .3163549    -2.06   0.039    -1.272344   -.0319123
                              Some college  |  -.6046705   .3172745    -1.91   0.057    -1.226689    .0173483
                                    2-year  |  -.4216347   .3295813    -1.28   0.201    -1.067781    .2245118
                                    4-year  |  -.2602047   .3194736    -0.81   0.415    -.8865349    .3661256
                                 Post-grad  |   .3692814   .3314204     1.11   0.265    -.2804706    1.019033
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .0310736   .1383598     0.22   0.822    -.2401818    .3023289
                                   Widowed  |   .0993844   .1646535     0.60   0.546      -.22342    .4221888
                             Never married  |   .4731616    .125424     3.77   0.000      .227267    .7190562
                Domestic/civil partnership  |   .6651547   .2419332     2.75   0.006      .190843    1.139467
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.1327773   .1425023    -0.93   0.352    -.4121541    .1465994
                                 $70k-$99k  |  -.2494653   .1666598    -1.50   0.135     -.576203    .0772724
                               $100k-$149k  |  -.2381929   .1720454    -1.38   0.166     -.575489    .0991032
                                   $150k +  |  -.0456523   .1925798    -0.24   0.813    -.4232063    .3319017
                         Prefer to not say  |  -.4900537   .1785651    -2.74   0.006    -.8401318   -.1399757
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |    .717769   .1334208     5.38   0.000     .4561967    .9793413
                                    Seldom  |   .8399074   .1224808     6.86   0.000     .5997829    1.080032
                                     Never  |   1.646454   .1177291    13.99   0.000     1.415646    1.877263
                      Don't know / Skipped  |   .4961048   .3636374     1.36   0.173    -.2168087    1.209018
                                            |
                                      _cons |  -1.543121   .3849992    -4.01   0.000    -2.297914   -.7883272
-------------------------------------------------------------------------------------------------------------

. estimates store f201

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1723133   .0267852     6.43   0.000      .135205    .2094216
          2  |   .3424786   .0331949    10.32   0.000     .2964904    .3884669
          3  |   .7593085    .031469    24.13   0.000     .7157112    .8029057
------------------------------------------------------------------------------

. 
. * 
. 
. codebook GENDER

-------------------------------------------------------------------------------------------------------------------
GENDER                                                                                                       Gender
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: gender_2020Sep

                 Range: [1,2]                         Units: 1
         Unique values: 2                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        2,866         1  Male
                        3,034         2  Female
                        6,617         .  

. 
. * GENDER == 1 : Men
. 
. svy, subpop(if GENDER == 1)      : logit VOTEBT ib2.FTIMMIG5          i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,693
Number of PSUs   = 4,693                          Population size = 4,608.2975
                                                  Subpop. no. obs =      2,130
                                                  Subpop. size    = 2,051.3356
                                                  Design df       =      4,692
                                                  F(31, 4662)     =       9.42
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -.7285004   .3527755    -2.07   0.039    -1.420106   -.0368947
                                     26/49  |   .2014457    .316839     0.64   0.525    -.4197075     .822599
                                   Missing  |   .4918798   .4202055     1.17   0.242    -.3319204     1.31568
                                     51/75  |   .8113698   .2452248     3.31   0.001      .330614    1.292126
                                     76/99  |   1.617972   .2447105     6.61   0.000     1.138224    2.097719
                                       100  |     1.5491   .3131883     4.95   0.000     .9351039    2.163096
                                            |
                                       RACE |
                                     Black  |   2.527652   .2915958     8.67   0.000     1.955987    3.099317
                                  Hispanic  |   .8978481   .2253647     3.98   0.000     .4560274    1.339669
                                     Asian  |    .623652   .4220603     1.48   0.140    -.2037844    1.451088
                                     Other  |  -.0207957   .2802427    -0.07   0.941     -.570203    .5286116
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.5589824   .2607901    -2.14   0.032    -1.070254   -.0477113
                                 Age 46/60  |  -.7248929   .2611763    -2.78   0.006    -1.236921   -.2128646
                                   Age 61+  |  -.6122929   .2643548    -2.32   0.021    -1.130552   -.0940333
                                            |
                                       EDUC |
                      High school graduate  |  -.6881162   .4272763    -1.61   0.107    -1.525778    .1495461
                              Some college  |  -.5540166   .4293045    -1.29   0.197    -1.395655    .2876219
                                    2-year  |  -.4209379   .4478251    -0.94   0.347    -1.298885    .4570097
                                    4-year  |  -.2378024   .4294699    -0.55   0.580    -1.079765    .6041603
                                 Post-grad  |   .2709986   .4421641     0.61   0.540    -.5958507    1.137848
                                            |
                                    MARITAL |
                      Separated / Divorced  |  -.1759835   .2193442    -0.80   0.422    -.6060011    .2540341
                                   Widowed  |  -.5303731   .3301184    -1.61   0.108     -1.17756     .116814
                             Never married  |   .3284392   .1790392     1.83   0.067    -.0225617    .6794401
                Domestic/civil partnership  |   .5078044   .3551571     1.43   0.153    -.1884702    1.204079
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.2981832   .2250715    -1.32   0.185     -.739429    .1430626
                                 $70k-$99k  |  -.3187349   .2535288    -1.26   0.209    -.8157704    .1783006
                               $100k-$149k  |  -.2256682   .2547037    -0.89   0.376    -.7250071    .2736708
                                   $150k +  |  -.2193931   .2711456    -0.81   0.418    -.7509658    .3121795
                         Prefer to not say  |  -.6331624   .2807806    -2.26   0.024    -1.183624   -.0827005
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |    .657732   .1978797     3.32   0.001     .2697949    1.045669
                                    Seldom  |   .9234244   .1897052     4.87   0.000     .5515132    1.295336
                                     Never  |   1.758985   .1779165     9.89   0.000     1.410186    2.107785
                      Don't know / Skipped  |   .3197207    .582551     0.55   0.583    -.8223529    1.461794
                                            |
                                      _cons |  -1.250298   .5473487    -2.28   0.022    -2.323359   -.1772378
-------------------------------------------------------------------------------------------------------------

. estimates store f202

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,693
Number of PSUs   = 4,693                          Population size = 4,608.2975
Model VCE: Linearized                             Design df       =      4,692

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1560584   .0365282     4.27   0.000     .1054527    .2066641
          2  |   .2770078     .04311     6.43   0.000     .2172838    .3367318
          3  |   .6433072   .0526457    12.22   0.000     .5703725    .7162419
------------------------------------------------------------------------------

. 
. * GENDER == 2 : Women
. 
. svy, subpop(if GENDER == 2)      : logit VOTEBT ib2.FTIMMIG5          i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,622
Number of PSUs   = 4,622                          Population size = 4,508.9276
                                                  Subpop. no. obs =      2,242
                                                  Subpop. size    = 2,122.8895
                                                  Design df       =      4,621
                                                  F(31, 4591)     =      12.36
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -1.142445   .3062517    -3.73   0.000    -1.742845   -.5420458
                                     26/49  |  -.1507897   .2644449    -0.57   0.569     -.669228    .3676485
                                   Missing  |   .3237697   .4026204     0.80   0.421    -.4655585    1.113098
                                     51/75  |   .8301717   .2290683     3.62   0.000     .3810885    1.279255
                                     76/99  |   1.510115   .2293821     6.58   0.000     1.060417    1.959814
                                       100  |    2.25816   .3155025     7.16   0.000     1.639625    2.876696
                                            |
                                       RACE |
                                     Black  |   3.389189   .3624661     9.35   0.000     2.678582    4.099796
                                  Hispanic  |   1.225954    .213727     5.74   0.000     .8069469    1.644961
                                     Asian  |   .8886009   .3365673     2.64   0.008     .2287684    1.548433
                                     Other  |   .2997684   .2685786     1.12   0.264    -.2267738    .8263106
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.3207735   .2230045    -1.44   0.150    -.7579688    .1164217
                                 Age 46/60  |  -.3785799   .2038612    -1.86   0.063    -.7782452    .0210854
                                   Age 61+  |  -.3297269   .2072633    -1.59   0.112    -.7360619    .0766082
                                            |
                                       EDUC |
                      High school graduate  |  -.6375958   .4243271    -1.50   0.133     -1.46948    .1942879
                              Some college  |  -.6884899   .4348003    -1.58   0.113    -1.540906    .1639264
                                    2-year  |  -.5093175   .4503984    -1.13   0.258    -1.392313    .3736784
                                    4-year  |  -.3332275   .4380954    -0.76   0.447    -1.192104    .5256487
                                 Post-grad  |   .4590395    .464703     0.99   0.323    -.4520003    1.370079
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .1962804   .1818467     1.08   0.280     -.160226    .5527868
                                   Widowed  |   .3904538   .1995196     1.96   0.050    -.0006999    .7816074
                             Never married  |   .6076938   .1679927     3.62   0.000     .2783478    .9370397
                Domestic/civil partnership  |   .8713069   .3238288     2.69   0.007     .2364478    1.506166
                                            |
                                   HHINCOME |
                                 $30k-$69k  |   .0477408   .1782656     0.27   0.789    -.3017448    .3972265
                                 $70k-$99k  |   -.129451   .2125026    -0.61   0.542    -.5460576    .2871555
                               $100k-$149k  |   -.254857   .2374179    -1.07   0.283    -.7203094    .2105954
                                   $150k +  |   .2172342   .2802239     0.78   0.438    -.3321385    .7666069
                         Prefer to not say  |  -.2917852   .2157467    -1.35   0.176    -.7147518    .1311814
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .8072066   .1790695     4.51   0.000     .4561448    1.158268
                                    Seldom  |   .7866727   .1600257     4.92   0.000     .4729459    1.100399
                                     Never  |   1.564328    .157984     9.90   0.000     1.254603    1.874052
                      Don't know / Skipped  |   .6931198   .4013547     1.73   0.084     -.093727    1.479967
                                            |
                                      _cons |  -1.272488   .5141227    -2.48   0.013    -2.280414    -.264562
-------------------------------------------------------------------------------------------------------------

. estimates store f203

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,622
Number of PSUs   = 4,622                          Population size = 4,508.9276
Model VCE: Linearized                             Design df       =      4,621

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |    .200371   .0357054     5.61   0.000     .1509051    .2498369
          2  |   .4399089   .0520068     8.46   0.000     .3678592    .5119586
          3  |    .882532   .0254679    34.65   0.000      .847249    .9178149
------------------------------------------------------------------------------

. 
. *
. 
. codebook AGEGRP

-------------------------------------------------------------------------------------------------------------------
AGEGRP                                                                                                RECODE of AGE
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (float)
                 Label: AGEGRP

                 Range: [1,4]                         Units: 1
         Unique values: 4                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        1,056         1  Age 18/30
                        1,182         2  Age 31/45
                        1,639         3  Age 46/60
                        2,023         4  Age 61+
                        6,617         .  

. 
. * AGEGRP == 1 : 18-30
. 
. svy, subpop(if   AGEGRP == 1)    : logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE          i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,737
Number of PSUs   = 4,737                          Population size = 4,546.4565
                                                  Subpop. no. obs =        520
                                                  Subpop. size    = 773.942003
                                                  Design df       =      4,736
                                                  F(29, 4708)     =       3.48
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -.9655238   .7361251    -1.31   0.190    -2.408671    .4776237
                                     26/49  |   .8944629   .5287569     1.69   0.091    -.1421465    1.931072
                                   Missing  |   .0107644   .8191865     0.01   0.990    -1.595222    1.616751
                                     51/75  |   1.504904   .4733266     3.18   0.001     .5769635    2.432844
                                     76/99  |   1.832294   .4748952     3.86   0.000     .9012784    2.763309
                                       100  |    3.01764   .7008085     4.31   0.000     1.643729     4.39155
                                            |
                                     GENDER |
                                    Female  |   .4830606   .2717005     1.78   0.075    -.0495988     1.01572
                                            |
                                       RACE |
                                     Black  |   2.233664   .6408416     3.49   0.000     .9773163    3.490011
                                  Hispanic  |   1.344328   .4364653     3.08   0.002     .4886526    2.200003
                                     Asian  |   .4237981   .4843498     0.87   0.382    -.5257527    1.373349
                                     Other  |   1.578759   .7438352     2.12   0.034     .1204961    3.037022
                                            |
                                       EDUC |
                      High school graduate  |  -.5775682    1.05134    -0.55   0.583    -2.638683    1.483547
                              Some college  |  -.4989727     1.0222    -0.49   0.625     -2.50296    1.505015
                                    2-year  |  -.9285148   1.059651    -0.88   0.381    -3.005923    1.148893
                                    4-year  |  -.1739096   1.045057    -0.17   0.868    -2.222707    1.874888
                                 Post-grad  |   1.310203    1.17706     1.11   0.266    -.9973812    3.617788
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .5368589   .8886242     0.60   0.546    -1.205258    2.278975
                                   Widowed  |   .4864108    .959439     0.51   0.612    -1.394536    2.367357
                             Never married  |   .8169519    .335694     2.43   0.015     .1588355    1.475068
                Domestic/civil partnership  |   1.357259   .7203404     1.88   0.060    -.0549431    2.769461
                                            |
                                   HHINCOME |
                                 $30k-$69k  |   .0012954   .4129186     0.00   0.997     -.808217    .8108079
                                 $70k-$99k  |  -.1149686   .5228976    -0.22   0.826    -1.140091    .9101539
                               $100k-$149k  |   .2216692   .5066724     0.44   0.662    -.7716444    1.214983
                                   $150k +  |   .0563528   .5555376     0.10   0.919    -1.032759    1.145465
                         Prefer to not say  |  -.1173557   .4490744    -0.26   0.794    -.9977503    .7630389
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   1.004153   .3861978     2.60   0.009     .2470255     1.76128
                                    Seldom  |   .5488461   .4067841     1.35   0.177    -.2486399    1.346332
                                     Never  |   1.662343   .3711044     4.48   0.000     .9348062    2.389881
                      Don't know / Skipped  |  -.0908484   .8283189    -0.11   0.913    -1.714739    1.533042
                                            |
                                      _cons |  -2.486396   1.220568    -2.04   0.042    -4.879277   -.0935157
-------------------------------------------------------------------------------------------------------------

. estimates store f204

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,737
Number of PSUs   = 4,737                          Population size = 4,546.4565
Model VCE: Linearized                             Design df       =      4,736

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1601688   .0866181     1.85   0.065     .0401694    .2801683
          2  |   .3337109   .0916584     3.64   0.000     .2067288     .460693
          3  |   .9110231   .0469468    19.41   0.000     .8459836    .9760625
------------------------------------------------------------------------------

. 
. * AGEGRP == 2 : 31-45
. 
. svy, subpop(if   AGEGRP == 2)    : logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE          i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,773
Number of PSUs   = 4,773                          Population size = 4,723.6411
                                                  Subpop. no. obs =        790
                                                  Subpop. size    = 963.840386
                                                  Design df       =      4,772
                                                  F(29, 4744)     =       5.76
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -1.308087   .4940064    -2.65   0.008    -2.276568   -.3396069
                                     26/49  |   -.322836    .436055    -0.74   0.459    -1.177705     .532033
                                   Missing  |    .812382   .5688363     1.43   0.153    -.3027995    1.927563
                                     51/75  |   .4625116   .3534169     1.31   0.191    -.2303485    1.155372
                                     76/99  |   1.713852   .3612758     4.74   0.000     1.005585     2.42212
                                       100  |   1.448956   .4837573     3.00   0.003     .5005689    2.397344
                                            |
                                     GENDER |
                                    Female  |   .4837303   .1981024     2.44   0.015     .0953583    .8721023
                                            |
                                       RACE |
                                     Black  |    2.98012   .4662992     6.39   0.000     2.065958    3.894281
                                  Hispanic  |   .7405917   .3125425     2.37   0.018     .1278643    1.353319
                                     Asian  |   1.286016   .6171813     2.08   0.037      .076056    2.495976
                                     Other  |   .5085203   .4723034     1.08   0.282    -.4174122    1.434453
                                            |
                                       EDUC |
                      High school graduate  |  -.8922025   .7130274    -1.25   0.211    -2.290065    .5056601
                              Some college  |  -.8210068   .7133656    -1.15   0.250    -2.219532    .5775189
                                    2-year  |  -.3434965   .7201063    -0.48   0.633    -1.755237    1.068244
                                    4-year  |   -.051621   .7189375    -0.07   0.943     -1.46107    1.357828
                                 Post-grad  |    .399068   .7615455     0.52   0.600    -1.093912    1.892048
                                            |
                                    MARITAL |
                      Separated / Divorced  |  -.1245979    .463557    -0.27   0.788    -1.033384    .7841877
                                   Widowed  |  -.2744955   .7063885    -0.39   0.698    -1.659343    1.110352
                             Never married  |   .1500134   .2429769     0.62   0.537    -.3263334    .6263602
                Domestic/civil partnership  |   .5551784   .4775333     1.16   0.245    -.3810072    1.491364
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.0174208   .3230436    -0.05   0.957    -.6507352    .6158936
                                 $70k-$99k  |  -.1754154   .3616871    -0.48   0.628    -.8844889     .533658
                               $100k-$149k  |   .1129333   .4057292     0.28   0.781     -.682483    .9083496
                                   $150k +  |   .0478653   .5036122     0.10   0.924    -.9394469    1.035178
                         Prefer to not say  |  -.9865717   .4300602    -2.29   0.022    -1.829688   -.1434554
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   1.012948   .3146312     3.22   0.001     .3961256     1.62977
                                    Seldom  |   1.093314   .3014323     3.63   0.000     .5023678    1.684261
                                     Never  |   2.215523   .2978339     7.44   0.000     1.631632    2.799415
                      Don't know / Skipped  |   1.184725   .5820647     2.04   0.042     .0436093     2.32584
                                            |
                                      _cons |  -1.995593   .7358354    -2.71   0.007     -3.43817   -.5530165
-------------------------------------------------------------------------------------------------------------

. estimates store f205

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,773
Number of PSUs   = 4,773                          Population size = 4,723.6411
Model VCE: Linearized                             Design df       =      4,772

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |    .131409   .0432359     3.04   0.002     .0715108    .1913073
          2  |   .3588245   .0716568     5.01   0.000     .2595524    .4580965
          3  |   .7044307   .0816892     8.62   0.000     .5912598    .8176015
------------------------------------------------------------------------------

. 
. * AGEGRP == 3 : 46-60
. 
. svy, subpop(if   AGEGRP == 3)    : logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE          i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,834
Number of PSUs   = 4,834                          Population size = 4,856.0795
                                                  Subpop. no. obs =      1,343
                                                  Subpop. size    = 1,080.1749
                                                  Design df       =      4,833
                                                  F(29, 4805)     =       7.51
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -.7073965   .3365889    -2.10   0.036    -1.367264   -.0475291
                                     26/49  |  -.4270607   .3709376    -1.15   0.250    -1.154267    .3001457
                                   Missing  |   .5228374    .468501     1.12   0.264    -.3956378    1.441313
                                     51/75  |   .7058474   .2701603     2.61   0.009     .1762103    1.235484
                                     76/99  |   1.594964   .2706443     5.89   0.000     1.064379     2.12555
                                       100  |   1.506881   .3347249     4.50   0.000     .8506683    2.163094
                                            |
                                     GENDER |
                                    Female  |   .7296911    .144207     5.06   0.000     .4469797    1.012403
                                            |
                                       RACE |
                                     Black  |   3.271584   .3878913     8.43   0.000     2.511141    4.032028
                                  Hispanic  |   1.686907   .2999371     5.62   0.000     1.098894    2.274921
                                     Asian  |   .8422723   .4279658     1.97   0.049     .0032646     1.68128
                                     Other  |   -.359486   .2923753    -1.23   0.219    -.9326745    .2137026
                                            |
                                       EDUC |
                      High school graduate  |  -.7714859   .6067927    -1.27   0.204    -1.961076    .4181037
                              Some college  |  -1.028195   .6143558    -1.67   0.094    -2.232612    .1762218
                                    2-year  |  -.3903836    .636035    -0.61   0.539    -1.637302    .8565344
                                    4-year  |  -.5756761   .6208836    -0.93   0.354     -1.79289    .6415383
                                 Post-grad  |   .3810869   .6397122     0.60   0.551    -.8730401    1.635214
                                            |
                                    MARITAL |
                      Separated / Divorced  |    -.14398   .2254128    -0.64   0.523    -.5858916    .2979316
                                   Widowed  |  -.2418489    .495444    -0.49   0.625    -1.213145    .7294468
                             Never married  |   .7346333   .2189864     3.35   0.001     .3053203    1.163946
                Domestic/civil partnership  |   .9746382   .3576392     2.73   0.006     .2735028    1.675774
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.2196548   .2523702    -0.87   0.384    -.7144152    .2751057
                                 $70k-$99k  |  -.3593832   .3197227    -1.12   0.261    -.9861852    .2674188
                               $100k-$149k  |  -.5878644   .3065682    -1.92   0.055    -1.188878    .0131488
                                   $150k +  |  -.0666281     .31692    -0.21   0.833    -.6879356    .5546793
                         Prefer to not say  |  -.6354728   .3125696    -2.03   0.042    -1.248251   -.0226943
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .7729302   .2546977     3.03   0.002     .2736067    1.272254
                                    Seldom  |   1.138498    .237868     4.79   0.000     .6721688    1.604828
                                     Never  |   1.846809   .2254451     8.19   0.000     1.404834    2.288784
                      Don't know / Skipped  |   .6569307   .4988702     1.32   0.188    -.3210819    1.634943
                                            |
                                      _cons |  -2.054233    .648324    -3.17   0.002    -3.325243   -.7832232
-------------------------------------------------------------------------------------------------------------

. estimates store f206

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,834
Number of PSUs   = 4,834                          Population size = 4,856.0795
Model VCE: Linearized                             Design df       =      4,833

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .2212837   .0410149     5.40   0.000     .1644624    .2781049
          2  |   .3656777    .055357     6.61   0.000     .2889871    .4423682
          3  |   .7223355    .049312    14.65   0.000     .6540197    .7906514
------------------------------------------------------------------------------

. 
. * AGEGRP == 4 : 61+
. 
. svy, subpop(if   AGEGRP == 4)    : logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE          i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,857
Number of PSUs   = 4,857                          Population size =  4,877.048
                                                  Subpop. no. obs =      1,719
                                                  Subpop. size    = 1,356.2679
                                                  Design df       =      4,856
                                                  F(29, 4828)     =       9.94
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -1.304944   .3662486    -3.56   0.000    -2.022957   -.5869314
                                     26/49  |   .0451317   .2974008     0.15   0.879    -.5379085     .628172
                                   Missing  |   .2657282   .4782618     0.56   0.579    -.6718814    1.203338
                                     51/75  |   .7525084   .2547248     2.95   0.003     .2531325    1.251884
                                     76/99  |   1.407654   .2491979     5.65   0.000     .9191132    1.896195
                                       100  |   1.809679   .3376212     5.36   0.000     1.147789    2.471569
                                            |
                                     GENDER |
                                    Female  |   .5283486   .1239131     4.26   0.000     .2854228    .7712743
                                            |
                                       RACE |
                                     Black  |   3.334251   .4135271     8.06   0.000     2.523551    4.144952
                                  Hispanic  |   .8132173   .2407835     3.38   0.001     .3411725    1.285262
                                     Asian  |   .5714184   .4637472     1.23   0.218     -.337736    1.480573
                                     Other  |  -.0038099    .284755    -0.01   0.989    -.5620586    .5544388
                                            |
                                       EDUC |
                      High school graduate  |  -.4038993   .3291205    -1.23   0.220    -1.049124    .2413258
                              Some college  |  -.1979022   .3347988    -0.59   0.554    -.8542595     .458455
                                    2-year  |   -.143953   .3581555    -0.40   0.688    -.8460998    .5581938
                                    4-year  |  -.1883501   .3449128    -0.55   0.585    -.8645354    .4878351
                                 Post-grad  |   .2928504    .362187     0.81   0.419    -.4172001    1.002901
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .1591517   .1780207     0.89   0.371    -.1898495    .5081528
                                   Widowed  |   .1317628   .1844389     0.71   0.475    -.2298209    .4933465
                             Never married  |   .6457933   .2167108     2.98   0.003      .220942    1.070645
                Domestic/civil partnership  |  -.0083456   .5335762    -0.02   0.988    -1.054396    1.037705
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.1058312   .1854668    -0.57   0.568    -.4694302    .2577678
                                 $70k-$99k  |  -.3041882   .2245598    -1.35   0.176     -.744427    .1360507
                               $100k-$149k  |  -.2992732   .2573882    -1.16   0.245    -.8038705    .2053242
                                   $150k +  |   .0297288   .3149766     0.09   0.925    -.5877679    .6472255
                         Prefer to not say  |  -.3206815   .2330108    -1.38   0.169     -.777488    .1361251
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .3677881   .1830952     2.01   0.045     .0088387    .7267374
                                    Seldom  |   .6823909   .1655681     4.12   0.000     .3578025    1.006979
                                     Never  |   1.319755   .1662832     7.94   0.000     .9937647    1.645745
                      Don't know / Skipped  |   .4764856   .6215583     0.77   0.443    -.7420501    1.695021
                                            |
                                      _cons |  -1.912855   .4087296    -4.68   0.000     -2.71415    -1.11156
-------------------------------------------------------------------------------------------------------------

. estimates store f207

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                           Number of obs   =     4,857
Number of PSUs   = 4,857                           Population size = 4,877.048
Model VCE: Linearized                              Design df       =     4,856

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1415681   .0346883     4.08   0.000     .0935117    .1896246
          2  |   .3781562   .0582865     6.49   0.000     .2974072    .4589051
          3  |   .7878973   .0433891    18.16   0.000      .727787    .8480077
------------------------------------------------------------------------------

. 
. *
. 
. codebook RACE

-------------------------------------------------------------------------------------------------------------------
RACE                                                                        RECODE of race_2020Sep (Race/ethnicity)
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: RACE

                 Range: [1,5]                         Units: 1
         Unique values: 5                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        4,059         1  White
                          664         2  Black
                          706         3  Hispanic
                          191         4  Asian
                          280         5  Other
                        6,617         .  

. 
. * RACE == 1 : Whites
. 
. svy, subpop(if   RACE == 1)      : logit VOTEBT ib2.FTIMMIG5 i.GENDER        i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,628
Number of PSUs   = 4,628                          Population size = 4,650.9896
                                                  Subpop. no. obs =      3,189
                                                  Subpop. size    = 2,809.0363
                                                  Design df       =      4,627
                                                  F(28, 4600)     =      18.51
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -1.267758   .2684126    -4.72   0.000    -1.793974   -.7415412
                                     26/49  |  -.2509549   .2107971    -1.19   0.234    -.6642177    .1623079
                                   Missing  |   .2988855   .3292417     0.91   0.364    -.3465853    .9443563
                                     51/75  |   .7027021   .1718945     4.09   0.000     .3657069    1.039697
                                     76/99  |   1.412776   .1737379     8.13   0.000     1.072167    1.753385
                                       100  |   1.879357   .2204262     8.53   0.000     1.447216    2.311497
                                            |
                                     GENDER |
                                    Female  |   .4820764   .0914909     5.27   0.000     .3027105    .6614422
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.3016452   .1872889    -1.61   0.107    -.6688207    .0655303
                                 Age 46/60  |  -.5398985    .176937    -3.05   0.002    -.8867793   -.1930176
                                   Age 61+  |  -.3085756   .1826687    -1.69   0.091    -.6666934    .0495421
                                            |
                                       EDUC |
                      High school graduate  |   .1845644   .3505119     0.53   0.599     -.502606    .8717348
                              Some college  |   .4528092    .348781     1.30   0.194     -.230968    1.136586
                                    2-year  |   .6142339   .3632762     1.69   0.091    -.0979608    1.326429
                                    4-year  |   .7580413   .3515973     2.16   0.031     .0687429     1.44734
                                 Post-grad  |   1.335161   .3639826     3.67   0.000     .6215815     2.04874
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .0970447   .1456973     0.67   0.505    -.1885916    .3826809
                                   Widowed  |   .1356977   .1892951     0.72   0.473    -.2354109    .5068063
                             Never married  |   .5968288   .1295807     4.61   0.000     .3427888    .8508688
                Domestic/civil partnership  |   .9697902   .2895585     3.35   0.001     .4021174    1.537463
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.0506611   .1602529    -0.32   0.752    -.3648332    .2635109
                                 $70k-$99k  |   -.134026   .1862854    -0.72   0.472    -.4992341    .2311822
                               $100k-$149k  |    -.09313   .1932342    -0.48   0.630    -.4719612    .2857011
                                   $150k +  |   .1977346   .2196234     0.90   0.368    -.2328321    .6283013
                         Prefer to not say  |   -.363045   .1908152    -1.90   0.057    -.7371337    .0110437
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .5860813   .1403417     4.18   0.000     .3109446     .861218
                                    Seldom  |   .8748666   .1316196     6.65   0.000     .6168294    1.132904
                                     Never  |   1.753933   .1258536    13.94   0.000       1.5072    2.000666
                      Don't know / Skipped  |   .3968731   .4556012     0.87   0.384    -.4963225    1.290069
                                            |
                                      _cons |  -2.588037   .4280241    -6.05   0.000    -3.427169   -1.748906
-------------------------------------------------------------------------------------------------------------

. estimates store f208

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,628
Number of PSUs   = 4,628                          Population size = 4,650.9896
Model VCE: Linearized                             Design df       =      4,627

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |    .089659   .0182758     4.91   0.000     .0643399    .1149781
          2  |   .2592159   .0294736     8.79   0.000     .2183835    .3000483
          3  |   .6962087   .0343176    20.29   0.000     .6486655     .743752
------------------------------------------------------------------------------

. 
. * RACENW == 1 : Non-Whites
. 
. svy, subpop(if   RACENW == 1)    : logit VOTEBT ib2.FTIMMIG5 i.GENDER        i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,687
Number of PSUs   = 4,687                          Population size = 4,466.2355
                                                  Subpop. no. obs =      1,183
                                                  Subpop. size    = 1,365.1888
                                                  Design df       =      4,686
                                                  F(28, 4659)     =       4.58
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |   -.417824   .4111898    -1.02   0.310    -1.223949    .3883013
                                     26/49  |   .2378921    .399771     0.60   0.552    -.5458471    1.021631
                                   Missing  |   .8475135   .5494392     1.54   0.123    -.2296457    1.924673
                                     51/75  |   .9742656    .349857     2.78   0.005     .2883814     1.66015
                                     76/99  |    1.69493   .3312761     5.12   0.000     1.045472    2.344387
                                       100  |   1.298615   .4531351     2.87   0.004     .4102571    2.186973
                                            |
                                     GENDER |
                                    Female  |   .8198458   .1772981     4.62   0.000     .4722581    1.167434
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.4963602   .3201571    -1.55   0.121    -1.124019    .1312983
                                 Age 46/60  |  -.3087813   .3053282    -1.01   0.312    -.9073681    .2898056
                                   Age 61+  |   -.333635   .3112344    -1.07   0.284    -.9438009    .2765308
                                            |
                                       EDUC |
                      High school graduate  |  -1.066585    .528592    -2.02   0.044    -2.102874   -.0302963
                              Some college  |  -1.252266   .5301847    -2.36   0.018    -2.291677   -.2128541
                                    2-year  |  -1.086983    .561318    -1.94   0.053     -2.18743     .013464
                                    4-year  |   -1.12171   .5372189    -2.09   0.037    -2.174912   -.0685086
                                 Post-grad  |  -.3977026   .5627022    -0.71   0.480    -1.500864    .7054584
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .0208491   .2920428     0.07   0.943    -.5516922    .5933903
                                   Widowed  |   .1019213    .381499     0.27   0.789    -.6459961    .8498387
                             Never married  |   .6011676   .2471588     2.43   0.015     .1166202    1.085715
                Domestic/civil partnership  |   .6126349   .3962034     1.55   0.122    -.1641102     1.38938
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.3084041   .2796666    -1.10   0.270    -.8566821     .239874
                                 $70k-$99k  |  -.6182251   .3120488    -1.98   0.048    -1.229988   -.0064626
                               $100k-$149k  |  -.8011166   .3633549    -2.20   0.028    -1.513463   -.0887701
                                   $150k +  |  -.6614686   .3874437    -1.71   0.088     -1.42104    .0981033
                         Prefer to not say  |   -.659375   .3274735    -2.01   0.044    -1.301377   -.0173729
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .7863578   .2584714     3.04   0.002     .2796323    1.293083
                                    Seldom  |   .6862412   .2526718     2.72   0.007     .1908855    1.181597
                                     Never  |   .9147217   .2441866     3.75   0.000      .436001    1.393442
                      Don't know / Skipped  |   .4480368    .710182     0.63   0.528    -.9442539    1.840328
                                            |
                                      _cons |   .4527399   .6652065     0.68   0.496    -.8513778    1.756858
-------------------------------------------------------------------------------------------------------------

. estimates store f209

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,687
Number of PSUs   = 4,687                          Population size = 4,466.2355
Model VCE: Linearized                             Design df       =      4,686

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .3962837   .0703108     5.64   0.000     .2988759    .4936914
          2  |   .4992125   .0728725     6.85   0.000     .3982557    .6001692
          3  |   .7850707    .057604    13.63   0.000     .7052668    .8648746
------------------------------------------------------------------------------

. 
. * 
. 
. codebook pid3_2020Sep

-------------------------------------------------------------------------------------------------------------------
pid3_2020Sep                                                                                      Party ID, 3-point
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (byte)
                 Label: pid3_2020Sep

                 Range: [1,5]                         Units: 1
         Unique values: 5                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                        2,270         1  Democrat
                        1,459         2  Republican
                        1,807         3  Independent
                          142         4  Other
                          222         5  Not sure
                        6,617         .  

. 
. * PID3 == 1 : Democrat
. 
. svy, subpop(if pid3_2020Sep == 1): logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND 
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,838
Number of PSUs   = 4,838                          Population size = 4,783.7955
                                                  Subpop. no. obs =      1,830
                                                  Subpop. size    =  1,600.932
                                                  Design df       =      4,837
                                                  F(32, 4806)     =       3.03
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -2.673901   .6700536    -3.99   0.000    -3.987511   -1.360292
                                     26/49  |  -.8819609   .6300358    -1.40   0.162    -2.117117    .3531957
                                   Missing  |  -.7831189   .8616335    -0.91   0.363    -2.472312    .9060744
                                     51/75  |  -.3120158   .5749067    -0.54   0.587    -1.439094    .8150627
                                     76/99  |   .5402681   .5895406     0.92   0.359    -.6154993    1.696036
                                       100  |   1.024021   .8211244     1.25   0.212    -.5857556    2.633798
                                            |
                                     GENDER |
                                    Female  |   .4385082   .2730051     1.61   0.108     -.096706    .9737223
                                            |
                                       RACE |
                                     Black  |   1.626521   .4653157     3.50   0.000     .7142913    2.538752
                                  Hispanic  |   .9079336   .4674867     1.94   0.052    -.0085529     1.82442
                                     Asian  |   1.319831   1.036791     1.27   0.203    -.7127496    3.352413
                                     Other  |    1.84385   .9022328     2.04   0.041     .0750641    3.612637
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.4423691   .5864234    -0.75   0.451    -1.592026    .7072873
                                 Age 46/60  |   .4249255   .6023016     0.71   0.481    -.7558595     1.60571
                                   Age 61+  |  -.1083971   .5985481    -0.18   0.856    -1.281823    1.065029
                                            |
                                       EDUC |
                      High school graduate  |   .3806335   .7354969     0.52   0.605    -1.061275    1.822542
                              Some college  |  -.1871876   .7651962    -0.24   0.807     -1.68732    1.312945
                                    2-year  |  -.0034874   .7835478    -0.00   0.996    -1.539597    1.532623
                                    4-year  |   .7588196   .8598005     0.88   0.378    -.9267802    2.444419
                                 Post-grad  |   .6078575    .858985     0.71   0.479    -1.076144    2.291859
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .3937047   .4457814     0.88   0.377    -.4802295    1.267639
                                   Widowed  |   .1632768   .5523263     0.30   0.768    -.9195338    1.246087
                             Never married  |   1.077991   .4278963     2.52   0.012     .2391202    1.916863
                Domestic/civil partnership  |   1.167387   .8825003     1.32   0.186    -.5627143    2.897489
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.6363757   .4260001    -1.49   0.135    -1.471529    .1987781
                                 $70k-$99k  |  -.3049591   .4898753    -0.62   0.534    -1.265337    .6554192
                               $100k-$149k  |  -.6183271   .5420076    -1.14   0.254    -1.680908    .4442542
                                   $150k +  |   .0381769   .7003907     0.05   0.957    -1.334907    1.411261
                         Prefer to not say  |   -.545542   .5374286    -1.02   0.310    -1.599146    .5080625
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .6889852   .4013309     1.72   0.086    -.0978058    1.475776
                                    Seldom  |   1.318721   .3951487     3.34   0.001     .5440498    2.093392
                                     Never  |   1.609582   .3849572     4.18   0.000     .8548911    2.364273
                      Don't know / Skipped  |    2.09115   1.382757     1.51   0.131    -.6196826    4.801983
                                            |
                                      _cons |   1.207053   1.083494     1.11   0.265    -.9170887    3.331194
-------------------------------------------------------------------------------------------------------------

. estimates store f210

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,838
Number of PSUs   = 4,838                          Population size = 4,783.7955
Model VCE: Linearized                             Design df       =      4,837

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .6429413   .0941018     6.83   0.000     .5125745    .7733081
          2  |   .9631039   .0188255    51.16   0.000     .9370234    .9891843
          3  |   .9864279   .0093642   105.34   0.000     .9734549     .999401
------------------------------------------------------------------------------

. 
. * PID3 == 3 : Independent
. 
. svy, subpop(if pid3_2020Sep == 3): logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND 
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,692
Number of PSUs   = 4,692                          Population size = 4,627.3911
                                                  Subpop. no. obs =      1,266
                                                  Subpop. size    =  1,137.928
                                                  Design df       =      4,691
                                                  F(32, 4660)     =       5.84
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -1.934634   .5275786    -3.67   0.000    -2.968936   -.9003321
                                     26/49  |  -.1827754   .3335185    -0.55   0.584    -.8366283    .4710776
                                   Missing  |  -.0003659   .4481802    -0.00   0.999    -.8790096    .8782778
                                     51/75  |   .9089196   .2668815     3.41   0.001     .3857064    1.432133
                                     76/99  |   1.418014   .2789096     5.08   0.000     .8712198    1.964807
                                       100  |   1.319707   .3403782     3.88   0.000     .6524056    1.987008
                                            |
                                     GENDER |
                                    Female  |   .2700077   .1502232     1.80   0.072    -.0245004    .5645157
                                            |
                                       RACE |
                                     Black  |   2.647305     .50918     5.20   0.000     1.649073    3.645537
                                  Hispanic  |   .5311701    .259926     2.04   0.041     .0215931    1.040747
                                     Asian  |   1.237991   .4802011     2.58   0.010     .2965715    2.179411
                                     Other  |  -.0841186   .2818321    -0.30   0.765    -.6366419    .4684047
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.5635027   .3076769    -1.83   0.067    -1.166694    .0396886
                                 Age 46/60  |   -1.01906   .2991781    -3.41   0.001     -1.60559   -.4325304
                                   Age 61+  |   -.773779   .3026541    -2.56   0.011    -1.367123   -.1804348
                                            |
                                       EDUC |
                      High school graduate  |   -.501248   .5725041    -0.88   0.381    -1.623625    .6211291
                              Some college  |   -.381473   .5714822    -0.67   0.504    -1.501847    .7389006
                                    2-year  |  -.3540727   .5898187    -0.60   0.548    -1.510394    .8022491
                                    4-year  |   .0972898   .5681068     0.17   0.864    -1.016466    1.211046
                                 Post-grad  |   .7445468   .5928952     1.26   0.209    -.4178062      1.9069
                                            |
                                    MARITAL |
                      Separated / Divorced  |  -.1890574   .2371631    -0.80   0.425    -.6540085    .2758937
                                   Widowed  |    .491188   .3273843     1.50   0.134    -.1506391    1.133015
                             Never married  |    .257159   .2095013     1.23   0.220    -.1535619    .6678799
                Domestic/civil partnership  |  -.1186457   .4005705    -0.30   0.767    -.9039521    .6666608
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.1664936   .2615421    -0.64   0.524     -.679239    .3462518
                                 $70k-$99k  |  -.4347714   .2912297    -1.49   0.136    -1.005718    .1361756
                               $100k-$149k  |  -.5799869   .3120938    -1.86   0.063    -1.191837    .0318636
                                   $150k +  |  -.0174782   .3424899    -0.05   0.959    -.6889193    .6539629
                         Prefer to not say  |   -.576199   .3046471    -1.89   0.059     -1.17345    .0210524
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .2838377   .2332982     1.22   0.224    -.1735364    .7412119
                                    Seldom  |   .7311775   .2056121     3.56   0.000     .3280812    1.134274
                                     Never  |   1.322153   .2120595     6.23   0.000     .9064162    1.737889
                      Don't know / Skipped  |   .0998473   .5391018     0.19   0.853    -.9570454     1.15674
                                            |
                                      _cons |  -.9342391   .7006108    -1.33   0.182    -2.307765    .4392872
-------------------------------------------------------------------------------------------------------------

. estimates store f211

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,692
Number of PSUs   = 4,692                          Population size = 4,627.3911
Model VCE: Linearized                             Design df       =      4,691

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .0684644   .0300814     2.28   0.023       .02679    .1101389
          2  |   .3371802   .0533456     6.32   0.000     .2632759    .4110846
          3  |   .6556167   .0576678    11.37   0.000     .5757245     .735509
------------------------------------------------------------------------------

. 
. * PID3 == 2 : Republican
. 
. svy, subpop(if pid3_2020Sep == 2): logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME
>  i.ATTEND
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,869
Number of PSUs   = 4,869                          Population size = 4,872.7345
                                                  Subpop. no. obs =      1,142
                                                  Subpop. size    = 1,281.3397
                                                  Design df       =      4,868
                                                  F(32, 4837)     =       2.67
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |   .3673087   .6768274     0.54   0.587    -.9595787    1.694196
                                     26/49  |   1.343213   .6405232     2.10   0.036     .0874983    2.598927
                                   Missing  |   .5279034   1.280545     0.41   0.680    -1.982543     3.03835
                                     51/75  |   1.058452   .5796724     1.83   0.068    -.0779679    2.194871
                                     76/99  |    1.24461    .578053     2.15   0.031     .1113657    2.377855
                                       100  |    1.45755   .9131757     1.60   0.111    -.3326862    3.247787
                                            |
                                     GENDER |
                                    Female  |      .4975   .3150004     1.58   0.114    -.1200431    1.115043
                                            |
                                       RACE |
                                     Black  |   2.405394   .5902073     4.08   0.000     1.248321    3.562467
                                  Hispanic  |   1.332588   .3946676     3.38   0.001     .5588612    2.106315
                                     Asian  |   .7818599   .6026948     1.30   0.195     -.399694    1.963414
                                     Other  |   .2936879    .649133     0.45   0.651    -.9789059    1.566282
                                            |
                                     AGEGRP |
                                 Age 31/45  |   .1708535   .4916307     0.35   0.728    -.7929646    1.134671
                                 Age 46/60  |  -.4244474   .4864046    -0.87   0.383     -1.37802    .5291251
                                   Age 61+  |  -.2700792   .4933492    -0.55   0.584    -1.237266    .6971078
                                            |
                                       EDUC |
                      High school graduate  |  -.8685727   .9442153    -0.92   0.358    -2.719661    .9825156
                              Some college  |  -1.094207   .9402851    -1.16   0.245     -2.93759    .7491765
                                    2-year  |  -.7239166   .9318015    -0.78   0.437    -2.550668    1.102835
                                    4-year  |  -.7214346   .9065924    -0.80   0.426    -2.498765    1.055896
                                 Post-grad  |   .0835456    .940249     0.09   0.929    -1.759767    1.926858
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .0144618    .501655     0.03   0.977    -.9690084     .997932
                                   Widowed  |  -1.762745   1.048212    -1.68   0.093    -3.817713    .2922226
                             Never married  |   .3254055   .4279177     0.76   0.447    -.5135063    1.164317
                Domestic/civil partnership  |   .9858271    .693056     1.42   0.155    -.3728755     2.34453
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.2514154   .4398441    -0.57   0.568    -1.113708    .6108776
                                 $70k-$99k  |   .5875853   .4592977     1.28   0.201    -.3128455    1.488016
                               $100k-$149k  |    .665365   .5533872     1.20   0.229    -.4195236    1.750254
                                   $150k +  |   .6850197   .5796398     1.18   0.237    -.4513359    1.821375
                         Prefer to not say  |  -1.418413   .8804743    -1.61   0.107     -3.14454    .3077139
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |  -.0492643   .4374658    -0.11   0.910    -.9068947    .8083662
                                    Seldom  |  -.4126941   .4702743    -0.88   0.380    -1.334644    .5092558
                                     Never  |   .7458193   .3409986     2.19   0.029     .0773082     1.41433
                      Don't know / Skipped  |  -.5049083   1.110501    -0.45   0.649    -2.681992    1.672175
                                            |
                                      _cons |  -4.000364   1.142542    -3.50   0.000    -6.240263   -1.760466
-------------------------------------------------------------------------------------------------------------

. estimates store f212

. margins, atmeans at(FTIMMIG5 = (0 2 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,869
Number of PSUs   = 4,869                          Population size = 4,872.7345
Model VCE: Linearized                             Design df       =      4,868

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |    .028494   .0123524     2.31   0.021     .0113812    .0456067
          2  |   .0199092   .0104485     1.91   0.057      .005434    .0343844
          3  |   .0802531   .0604502     1.33   0.184    -.0034934    .1639995
------------------------------------------------------------------------------

. 
. *****************************************************************************************************************
> *
. * Figure 3. Absolute measure [using Nov 2020 weights]
. *****************************************************************************************************************
> *
. 
. svyset [pw = weight_genpop_2020Nov]

Sampling weights: weight_genpop_2020Nov
             VCE: linearized
     Single unit: missing
        Strata 1: <one>
 Sampling unit 1: <observations>
           FPC 1: <zero>

. 
. codebook FTIMMIG5

-------------------------------------------------------------------------------------------------------------------
FTIMMIG5                                            RECODE of ft_immig_2020Sep (Feeling thermometer for immigrants)
-------------------------------------------------------------------------------------------------------------------

                  Type: Numeric (int)
                 Label: FT5

                 Range: [0,6]                         Units: 1
         Unique values: 7                         Missing .: 6,617/12,517

            Tabulation: Freq.   Numeric  Label
                          444         0  0/25
                          574         1  26/49
                          518         2  50
                          267         3  Missing
                        1,548         4  51/75
                        2,088         5  76/99
                          461         6  100
                        6,617         .  

. 
. * Controls for demographics
. 
. svy: logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME i.ATTEND i.STATE
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(82, 4290)     =       9.38
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |   -.991031   .2442585    -4.06   0.000    -1.469901   -.5121606
                                     26/49  |  -.0563476   .2080699    -0.27   0.787    -.4642702    .3515749
                                   Missing  |   .4241847    .277491     1.53   0.126    -.1198382    .9682076
                                     51/75  |   .7933348   .1684768     4.71   0.000     .4630348    1.123635
                                     76/99  |   1.560561   .1672351     9.33   0.000     1.232696    1.888427
                                       100  |   1.764126   .2218176     7.95   0.000     1.329251    2.199001
                                            |
                                     GENDER |
                                    Female  |   .5977264   .0858065     6.97   0.000     .4295021    .7659506
                                            |
                                       RACE |
                                     Black  |   2.924696   .2268452    12.89   0.000     2.479964    3.369428
                                  Hispanic  |   1.070803   .1628378     6.58   0.000     .7515584    1.390048
                                     Asian  |   .7471064   .2930089     2.55   0.011     .1726605    1.321552
                                     Other  |   .0952538   .1882986     0.51   0.613    -.2739069    .4644144
                                            |
                                     AGEGRP |
                                 Age 31/45  |   -.433562   .1720407    -2.52   0.012     -.770849   -.0962749
                                 Age 46/60  |  -.5543728   .1689567    -3.28   0.001    -.8856135    -.223132
                                   Age 61+  |  -.4341141    .171751    -2.53   0.012     -.770833   -.0973951
                                            |
                                       EDUC |
                      High school graduate  |   -.592371   .3265075    -1.81   0.070    -1.232491    .0477492
                              Some college  |  -.5252207   .3279051    -1.60   0.109    -1.168081    .1176394
                                    2-year  |   -.360428   .3413567    -1.06   0.291     -1.02966    .3088041
                                    4-year  |  -.1924994   .3313504    -0.58   0.561    -.8421141    .4571153
                                 Post-grad  |   .4280063   .3417547     1.25   0.210     -.242006    1.098019
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .0375951   .1415768     0.27   0.791    -.2399671    .3151573
                                   Widowed  |   .0853817   .1680319     0.51   0.611     -.244046    .4148095
                             Never married  |   .4836871   .1243071     3.89   0.000     .2399822    .7273919
                Domestic/civil partnership  |   .6548526   .2484362     2.64   0.008     .1677917    1.141913
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.1189845    .141853    -0.84   0.402    -.3970883    .1591193
                                 $70k-$99k  |  -.2829598   .1698182    -1.67   0.096    -.6158895      .04997
                               $100k-$149k  |  -.2560698   .1756646    -1.46   0.145    -.6004615    .0883218
                                   $150k +  |   -.122436   .1993456    -0.61   0.539    -.5132544    .2683825
                         Prefer to not say  |  -.5164479   .1757505    -2.94   0.003     -.861008   -.1718879
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .7571369    .134917     5.61   0.000     .4926312    1.021643
                                    Seldom  |   .8704038   .1251993     6.95   0.000     .6249496    1.115858
                                     Never  |   1.682265   .1199184    14.03   0.000     1.447164    1.917366
                      Don't know / Skipped  |   .6282228   .3538205     1.78   0.076    -.0654446     1.32189
                                            |
                                      STATE |
                                    Alaska  |   .5668428   .6752983     0.84   0.401    -.7570841     1.89077
                                   Arizona  |   -.611652   .4457331    -1.37   0.170    -1.485515    .2622108
                                  Arkansas  |  -.8392983   .5086127    -1.65   0.099    -1.836437    .1578405
                                California  |  -.1320143   .3503707    -0.38   0.706    -.8189185    .5548898
                                  Colorado  |  -.1699789   .4152631    -0.41   0.682     -.984105    .6441473
                               Connecticut  |   -.225419   .5309611    -0.42   0.671    -1.266372    .8155339
                                  Delaware  |   -.021126   .9107147    -0.02   0.981    -1.806588    1.764336
                      District of Columbia  |   1.048911   1.201442     0.87   0.383    -1.306524    3.404346
                                   Florida  |  -1.014903   .3690738    -2.75   0.006    -1.738475   -.2913312
                                   Georgia  |  -.8623174   .4147948    -2.08   0.038    -1.675526   -.0491094
                                    Hawaii  |  -.6743193   .8342612    -0.81   0.419    -2.309894    .9612556
                                     Idaho  |  -.6164326   .4638232    -1.33   0.184    -1.525761    .2928959
                                  Illinois  |  -.2916611   .4001061    -0.73   0.466    -1.076072    .4927496
                                   Indiana  |  -.0768286   .4087726    -0.19   0.851    -.8782301     .724573
                                      Iowa  |   .0615188   .4417285     0.14   0.889    -.8044929    .9275305
                                    Kansas  |  -.1243558   .4976984    -0.25   0.803    -1.100097    .8513853
                                  Kentucky  |  -.5963563   .5055055    -1.18   0.238    -1.587403    .3946907
                                 Louisiana  |  -.4953024   .4531183    -1.09   0.274    -1.383644    .3930392
                                     Maine  |   .4122586   .5567765     0.74   0.459    -.6793054    1.503823
                                  Maryland  |   .1902588   .4304279     0.44   0.658     -.653598    1.034116
                             Massachusetts  |  -.0165555   .4777961    -0.03   0.972     -.953278     .920167
                                  Michigan  |  -.4660383   .4030566    -1.16   0.248    -1.256233     .324157
                                 Minnesota  |  -.5433309   .4143729    -1.31   0.190    -1.355712    .2690501
                               Mississippi  |  -.7549122   .5195611    -1.45   0.146    -1.773515    .2636909
                                  Missouri  |  -.5854594   .4244254    -1.38   0.168    -1.417548    .2466296
                                   Montana  |  -1.043928   .6490655    -1.61   0.108    -2.316425    .2285698
                                  Nebraska  |  -.8734408   .5297308    -1.65   0.099    -1.911982       .1651
                                    Nevada  |  -1.070474   .5515923    -1.94   0.052    -2.151874    .0109266
                             New Hampshire  |  -.2241756   .5964286    -0.38   0.707    -1.393478    .9451269
                                New Jersey  |  -.6156682   .3813975    -1.61   0.107    -1.363401    .1320642
                                New Mexico  |  -.8741297   .5868768    -1.49   0.136    -2.024706    .2764462
                                  New York  |   .1637411   .3654722     0.45   0.654    -.5527695    .8802518
                            North Carolina  |  -.4850447   .4272545    -1.14   0.256     -1.32268    .3525906
                              North Dakota  |  -.5869694   .9494603    -0.62   0.536    -2.448393    1.274454
                                      Ohio  |   -.140238   .3922471    -0.36   0.721    -.9092412    .6287652
                                  Oklahoma  |  -1.019022   .5147061    -1.98   0.048    -2.028107   -.0099372
                                    Oregon  |  -.2019631   .4445348    -0.45   0.650    -1.073477    .6695504
                              Pennsylvania  |  -.2359646    .357511    -0.66   0.509    -.9368673     .464938
                              Rhode Island  |   .0652867   .7193381     0.09   0.928    -1.344981    1.475554
                            South Carolina  |  -.4046578   .4523136    -0.89   0.371    -1.291422     .482106
                              South Dakota  |  -1.563512   .6829432    -2.29   0.022    -2.902427   -.2245971
                                 Tennessee  |  -.9586648   .4458187    -2.15   0.032    -1.832695   -.0846343
                                     Texas  |  -.1754674   .3711331    -0.47   0.636    -.9030764    .5521416
                                      Utah  |  -.0347051   .4684079    -0.07   0.941    -.9530219    .8836118
                                   Vermont  |   .3707751   .7646245     0.48   0.628    -1.128276    1.869827
                                  Virginia  |  -.1896297   .3969171    -0.48   0.633    -.9677884    .5885289
                                Washington  |  -.0753389   .4033669    -0.19   0.852    -.8661425    .7154648
                             West Virginia  |  -.3673765   .5181395    -0.71   0.478    -1.383193    .6484395
                                 Wisconsin  |  -.4056052   .3969751    -1.02   0.307    -1.183878    .3726672
                                   Wyoming  |   .0879826   .6444446     0.14   0.891    -1.175456    1.351421
                                            |
                                      _cons |  -1.268598   .5041122    -2.52   0.012    -2.256913   -.2802825
-------------------------------------------------------------------------------------------------------------

. estimates store f31

. margins, atmeans at(FTIMMIG5 = (0 1 2 4 5 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1642595   .0261561     6.28   0.000     .1280228    .2004962
          2  |   .3335466   .0318631    10.47   0.000     .2894034    .3776898
          3  |   .3461875   .0338598    10.22   0.000     .2992781    .3930969
          4  |   .5392925   .0197788    27.27   0.000     .5118909    .5666941
          5  |   .7160031   .0159261    44.96   0.000     .6939391    .7380671
          6  |   .7555224   .0305318    24.75   0.000     .7132236    .7978213
------------------------------------------------------------------------------

. 
. * Controls for demographics and partisanship
. 
. svy: logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME i.ATTEND i.STATE ib4.PID7
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(89, 4283)     =      13.62
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -1.870828   .4075137    -4.59   0.000    -2.669762   -1.071895
                                     26/49  |   .0029216   .3045405     0.01   0.992    -.5941322    .5999754
                                   Missing  |    .008003   .4403251     0.02   0.985    -.8552574    .8712633
                                     51/75  |   .5143989   .2413618     2.13   0.033     .0412075    .9875903
                                     76/99  |   .8793684   .2413823     3.64   0.000     .4061367      1.3526
                                       100  |   .8714321   .3352964     2.60   0.009     .2140813    1.528783
                                            |
                                     GENDER |
                                    Female  |   .5141503   .1450622     3.54   0.000     .2297549    .7985457
                                            |
                                       RACE |
                                     Black  |   1.684011   .3571389     4.72   0.000     .9838374    2.384184
                                  Hispanic  |   1.142431   .2453997     4.66   0.000     .6613231    1.623539
                                     Asian  |   1.107731   .3654538     3.03   0.002     .3912563    1.824205
                                     Other  |   .2010231   .2355745     0.85   0.394    -.2608223    .6628686
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.1969597   .2914201    -0.68   0.499    -.7682908    .3743713
                                 Age 46/60  |  -.1631972    .291739    -0.56   0.576    -.7351536    .4087591
                                   Age 61+  |  -.2426701   .3023203    -0.80   0.422     -.835371    .3500309
                                            |
                                       EDUC |
                      High school graduate  |  -.0070134   .5861306    -0.01   0.990    -1.156126      1.1421
                              Some college  |  -.2931232   .5741195    -0.51   0.610    -1.418688     .832442
                                    2-year  |  -.4982503   .6051366    -0.82   0.410    -1.684625    .6881241
                                    4-year  |   .0331639    .588345     0.06   0.955     -1.12029    1.186618
                                 Post-grad  |     .50369   .6069525     0.83   0.407    -.6862444    1.693625
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .1624522   .2344873     0.69   0.488    -.2972617    .6221662
                                   Widowed  |   .1987256    .270246     0.74   0.462    -.3310935    .7285446
                             Never married  |   .8715496   .2107044     4.14   0.000     .4584622    1.284637
                Domestic/civil partnership  |   .6968841   .5113878     1.36   0.173    -.3056952    1.699463
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.0187693   .2330914    -0.08   0.936    -.4757466     .438208
                                 $70k-$99k  |   .3445175   .2669598     1.29   0.197     -.178859     .867894
                               $100k-$149k  |   .1125994   .3141419     0.36   0.720    -.5032779    .7284767
                                   $150k +  |   .7125316   .3536091     2.02   0.044     .0192786    1.405785
                         Prefer to not say  |  -.1579046   .2957615    -0.53   0.593     -.737747    .4219379
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .4364543   .2479454     1.76   0.078    -.0496444    .9225529
                                    Seldom  |   .6996619   .2220067     3.15   0.002     .2644163    1.134907
                                     Never  |   1.001238   .2314897     4.33   0.000     .5474011    1.455075
                      Don't know / Skipped  |   .7073282   .4148958     1.70   0.088    -.1060779    1.520734
                                            |
                                      STATE |
                                    Alaska  |  -.1386799   1.031747    -0.13   0.893    -2.161427    1.884067
                                   Arizona  |   -1.22457   .7068304    -1.73   0.083    -2.610316    .1611758
                                  Arkansas  |   .1900791   .8732494     0.22   0.828    -1.521932    1.902091
                                California  |  -.7047489   .6383161    -1.10   0.270    -1.956172    .5466742
                                  Colorado  |  -.0189722   .7140886    -0.03   0.979    -1.418948    1.381003
                               Connecticut  |  -.2545023   .7341653    -0.35   0.729    -1.693838    1.184834
                                  Delaware  |   .0739499   1.156616     0.06   0.949    -2.193604    2.341504
                      District of Columbia  |  -.6156792   2.304254    -0.27   0.789    -5.133184    3.901826
                                   Florida  |  -1.277235   .6053663    -2.11   0.035    -2.464059   -.0904099
                                   Georgia  |  -.4717218   .6423616    -0.73   0.463    -1.731076    .7876325
                                    Hawaii  |   .0175106   1.003753     0.02   0.986    -1.950354    1.985375
                                     Idaho  |  -.5330923   .7144482    -0.75   0.456    -1.933773    .8675883
                                  Illinois  |  -.9022042   .7082964    -1.27   0.203    -2.290824    .4864159
                                   Indiana  |  -.5519142   .6934956    -0.80   0.426    -1.911517    .8076886
                                      Iowa  |  -.3746297    .735253    -0.51   0.610    -1.816098    1.066839
                                    Kansas  |   .7904672   .7297664     1.08   0.279    -.6402449    2.221179
                                  Kentucky  |  -2.099599   .8796936    -2.39   0.017    -3.824244   -.3749537
                                 Louisiana  |   -.531211   .7710239    -0.69   0.491    -2.042809    .9803867
                                     Maine  |  -1.149947   1.060626    -1.08   0.278    -3.229311    .9294173
                                  Maryland  |   -.472768   .7488188    -0.63   0.528    -1.940833    .9952964
                             Massachusetts  |  -.4196808   .6718198    -0.62   0.532    -1.736788    .8974264
                                  Michigan  |  -1.778909   .8148182    -2.18   0.029    -3.376366   -.1814526
                                 Minnesota  |  -.3387539   .7908393    -0.43   0.668      -1.8892    1.211692
                               Mississippi  |  -.4423301   .8583774    -0.52   0.606    -2.125185    1.240525
                                  Missouri  |  -.6871461   .7384955    -0.93   0.352    -2.134972    .7606794
                                   Montana  |  -2.035301   .7026829    -2.90   0.004    -3.412915    -.657686
                                  Nebraska  |  -1.275686   .9498807    -1.34   0.179    -3.137934    .5865611
                                    Nevada  |  -2.133726   .7608402    -2.80   0.005    -3.625358   -.6420933
                             New Hampshire  |  -.7875826   .9075331    -0.87   0.386    -2.566808    .9916423
                                New Jersey  |  -1.473086   .7505737    -1.96   0.050    -2.944591   -.0015811
                                New Mexico  |   -1.92418   .8972826    -2.14   0.032    -3.683308   -.1650509
                                  New York  |  -.3611631   .6711913    -0.54   0.591    -1.677038    .9547121
                            North Carolina  |  -1.810448   .7454091    -2.43   0.015    -3.271827    -.349068
                              North Dakota  |  -1.229327   .8363382    -1.47   0.142    -2.868974    .4103193
                                      Ohio  |  -1.344398   .7113319    -1.89   0.059    -2.738969    .0501727
                                  Oklahoma  |  -1.016528   1.437496    -0.71   0.480     -3.83475    1.801693
                                    Oregon  |   -1.04484   .8556048    -1.22   0.222    -2.722259    .6325793
                              Pennsylvania  |  -1.397613   .6444736    -2.17   0.030    -2.661108   -.1341176
                              Rhode Island  |  -.2642911   1.572819    -0.17   0.867    -3.347814    2.819232
                            South Carolina  |  -.2956167   .7940387    -0.37   0.710    -1.852335    1.261102
                              South Dakota  |  -2.021762   1.280709    -1.58   0.114    -4.532601    .4890771
                                 Tennessee  |  -.9369177   .7470045    -1.25   0.210    -2.401425    .5275898
                                     Texas  |      -.447   .6637877    -0.67   0.501     -1.74836    .8543604
                                      Utah  |   .1264749   .7860326     0.16   0.872    -1.414547    1.667497
                                   Vermont  |  -.4166055   .9530193    -0.44   0.662    -2.285006    1.451795
                                  Virginia  |  -.5762362   .7232934    -0.80   0.426    -1.994258    .8417855
                                Washington  |  -.2754184   .6543527    -0.42   0.674    -1.558281    1.007445
                             West Virginia  |  -1.682597   .9359097    -1.80   0.072    -3.517454    .1522607
                                 Wisconsin  |  -.6447705   .6816988    -0.95   0.344    -1.981246    .6917045
                                   Wyoming  |   .5758044   .7536507     0.76   0.445     -.901733    2.053342
                                            |
                                       PID7 |
                           Strong Democrat  |   4.278233   .3028329    14.13   0.000     3.684527    4.871939
                  Not very strong Democrat  |   2.297012   .2118171    10.84   0.000     1.881743    2.712281
                             Lean Democrat  |   3.940323   .3986498     9.88   0.000     3.158768    4.721879
                           Lean Republican  |   -2.81538   .3006838    -9.36   0.000    -3.404873   -2.225888
                Not very strong Republican  |  -1.640749   .2170683    -7.56   0.000    -2.066313   -1.215185
                         Strong Republican  |  -3.668974   .3206246   -11.44   0.000    -4.297561   -3.040388
                                  Not sure  |   .0887494    .446148     0.20   0.842    -.7859269    .9634256
                                            |
                                      _cons |  -1.225438   .8786312    -1.39   0.163       -2.948    .4971247
-------------------------------------------------------------------------------------------------------------

. estimates store f32

. margins, atmeans at(FTIMMIG5 = (0 1 2 4 5 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1247893   .0394268     3.17   0.002     .0701673    .1794114
          2  |   .4814865   .0649648     7.41   0.000      .391484     .571489
          3  |   .4807571    .055293     8.69   0.000      .404154    .5573602
          4  |   .6076368   .0375544    16.18   0.000     .5556088    .6596648
          5  |   .6904788   .0303076    22.78   0.000     .6484907     .732467
          6  |   .6887802   .0560713    12.28   0.000     .6110989    .7664615
------------------------------------------------------------------------------

. 
. * Controls for demographics, partisanship, and other groups
. 
. svy: logit VOTEBT ib2.FTIMMIG5 i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME i.ATTEND i.STATE ib4.PID7 ib2
> .FTWHITE5 ib2.FTBLACK5 ib2.FTHISPN5 ib2.FTASIAN5 ib2.FTBLM5 ib2.FTGAY5 ib2.FTMUSLM5 ib2.FTPOLICE5
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(137, 4235)    =       8.02
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                   FTIMMIG5 |
                                      0/25  |  -1.855198   .5721084    -3.24   0.001    -2.976821   -.7335761
                                     26/49  |  -.1363316   .4290357    -0.32   0.751     -.977459    .7047958
                                   Missing  |   .8637206   .6850365     1.26   0.207    -.4792983    2.206739
                                     51/75  |   .0953062   .3662924     0.26   0.795    -.6228125     .813425
                                     76/99  |   .9269008   .4190839     2.21   0.027      .105284    1.748518
                                       100  |   1.646032   .7315095     2.25   0.024     .2119029    3.080162
                                            |
                                     GENDER |
                                    Female  |   .3944737   .1937113     2.04   0.042     .0147014    .7742461
                                            |
                                       RACE |
                                     Black  |   .4697553    .425833     1.10   0.270    -.3650931    1.304604
                                  Hispanic  |   .8619497    .316065     2.73   0.006      .242302    1.481597
                                     Asian  |   .2503916    .489968     0.51   0.609     -.710194    1.210977
                                     Other  |   .2798978   .2607036     1.07   0.283    -.2312133     .791009
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.2112988   .3581466    -0.59   0.555    -.9134477    .4908501
                                 Age 46/60  |   .4913904    .349687     1.41   0.160    -.1941734    1.176954
                                   Age 61+  |   .8334471   .3771937     2.21   0.027     .0939562    1.572938
                                            |
                                       EDUC |
                      High school graduate  |  -.4284419   .7886363    -0.54   0.587    -1.974569    1.117685
                              Some college  |  -.6890875   .8053745    -0.86   0.392     -2.26803    .8898547
                                    2-year  |  -.9491878   .8403638    -1.13   0.259    -2.596727    .6983513
                                    4-year  |  -.4827327   .8006799    -0.60   0.547    -2.052471    1.087006
                                 Post-grad  |  -.1563901   .8260769    -0.19   0.850     -1.77592    1.463139
                                            |
                                    MARITAL |
                      Separated / Divorced  |    .228348   .2808753     0.81   0.416      -.32231     .779006
                                   Widowed  |   .2303855   .3420576     0.67   0.501    -.4402209    .9009918
                             Never married  |   .8812862   .2783648     3.17   0.002     .3355502    1.427022
                Domestic/civil partnership  |   .5587645   .8248323     0.68   0.498    -1.058325    2.175854
                                            |
                                   HHINCOME |
                                 $30k-$69k  |   .5774128   .2992302     1.93   0.054    -.0092301    1.164056
                                 $70k-$99k  |    1.01275   .3377876     3.00   0.003     .3505149    1.674985
                               $100k-$149k  |    .768559   .3636879     2.11   0.035     .0555464    1.481572
                                   $150k +  |   1.446083   .4502886     3.21   0.001      .563289    2.328877
                         Prefer to not say  |   .2768685   .3974591     0.70   0.486    -.5023528     1.05609
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .5519046   .3143203     1.76   0.079    -.0643225    1.168132
                                    Seldom  |   .8177851   .3038239     2.69   0.007     .2221362    1.413434
                                     Never  |   1.242464   .2816088     4.41   0.000     .6903679     1.79456
                      Don't know / Skipped  |    .613344   .6147922     1.00   0.319    -.5919603    1.818648
                                            |
                                      STATE |
                                    Alaska  |  -.7726499    1.15172    -0.67   0.502    -3.030606    1.485306
                                   Arizona  |  -1.437113   .6197589    -2.32   0.020    -2.652154    -.222071
                                  Arkansas  |   .2237678   .8070582     0.28   0.782    -1.358475    1.806011
                                California  |  -1.329597   .6334389    -2.10   0.036    -2.571458   -.0877354
                                  Colorado  |   -.761515   .7964383    -0.96   0.339    -2.322938    .7999078
                               Connecticut  |  -.5393889   .7768816    -0.69   0.488    -2.062471    .9836929
                                  Delaware  |   .0289167   .8712333     0.03   0.974    -1.679142    1.736976
                      District of Columbia  |  -.4901393   2.055198    -0.24   0.812     -4.51937    3.539091
                                   Florida  |  -1.768326   .5637568    -3.14   0.002    -2.873575   -.6630768
                                   Georgia  |  -.9796399    .609767    -1.61   0.108    -2.175092    .2158124
                                    Hawaii  |  -.5539392   .9563562    -0.58   0.562    -2.428882    1.321004
                                     Idaho  |  -1.428336   1.021266    -1.40   0.162    -3.430535    .5738625
                                  Illinois  |  -1.251243   .7021336    -1.78   0.075     -2.62778    .1252951
                                   Indiana  |   -.786782   .6722602    -1.17   0.242    -2.104753    .5311887
                                      Iowa  |  -.8948639   .9137466    -0.98   0.327     -2.68627    .8965427
                                    Kansas  |    .887425   .7525904     1.18   0.238    -.5880336    2.362884
                                  Kentucky  |  -2.629698   1.406203    -1.87   0.062    -5.386569    .1271722
                                 Louisiana  |  -1.218582   .8051609    -1.51   0.130    -2.797105     .359942
                                     Maine  |  -2.465422   1.375575    -1.79   0.073    -5.162246    .2314023
                                  Maryland  |  -1.115383   .6884132    -1.62   0.105    -2.465022    .2342559
                             Massachusetts  |  -.8152989   .6991872    -1.17   0.244     -2.18606    .5554623
                                  Michigan  |  -2.971501   .8704908    -3.41   0.001    -4.678105   -1.264898
                                 Minnesota  |  -1.539615   .9012397    -1.71   0.088    -3.306502    .2272716
                               Mississippi  |  -1.654441   1.612588    -1.03   0.305    -4.815932    1.507049
                                  Missouri  |  -.8711068   .6488712    -1.34   0.180    -2.143223    .4010096
                                   Montana  |   -3.59383   .8828367    -4.07   0.000    -5.324637   -1.863022
                                  Nebraska  |  -1.383529   1.306762    -1.06   0.290    -3.945444    1.178387
                                    Nevada  |  -2.891702   .8772689    -3.30   0.001    -4.611594   -1.171811
                             New Hampshire  |  -1.125769   .9425446    -1.19   0.232    -2.973634    .7220963
                                New Jersey  |  -2.652792   .6942052    -3.82   0.000    -4.013786   -1.291798
                                New Mexico  |  -2.053389   .9512118    -2.16   0.031    -3.918246   -.1885314
                                  New York  |  -1.155636   .5949434    -1.94   0.052    -2.322027    .0107547
                            North Carolina  |  -2.660517   .7428964    -3.58   0.000    -4.116971   -1.204064
                              North Dakota  |   .0663043     .98264     0.07   0.946    -1.860168    1.992777
                                      Ohio  |  -1.360644   .7311601    -1.86   0.063    -2.794089    .0728001
                                  Oklahoma  |  -2.477082   .8644306    -2.87   0.004    -4.171804   -.7823596
                                    Oregon  |  -1.411322   .8625753    -1.64   0.102    -3.102407    .2797623
                              Pennsylvania  |  -1.593794    .597722    -2.67   0.008    -2.765632   -.4219556
                              Rhode Island  |  -.4466605   1.364497    -0.33   0.743    -3.121765    2.228444
                            South Carolina  |  -1.840324   .9689085    -1.90   0.058    -3.739875     .059228
                              South Dakota  |  -2.360504   1.429501    -1.65   0.099    -5.163052    .4420432
                                 Tennessee  |  -2.140349   .8091066    -2.65   0.008    -3.726608     -.55409
                                     Texas  |  -1.123904   .6768049    -1.66   0.097    -2.450785    .2029768
                                      Utah  |  -.3956067    .715254    -0.55   0.580    -1.797867    1.006654
                                   Vermont  |  -.7042796   1.075448    -0.65   0.513    -2.812703    1.404144
                                  Virginia  |  -1.311012   1.008483    -1.30   0.194    -3.288149    .6661255
                                Washington  |   -.316386   .6493363    -0.49   0.626    -1.589414    .9566423
                             West Virginia  |  -.1836753   .9261963    -0.20   0.843     -1.99949    1.632139
                                 Wisconsin  |  -.8460341   .6135923    -1.38   0.168    -2.048986    .3569178
                                   Wyoming  |   .0879662   .8031373     0.11   0.913     -1.48659    1.662522
                                            |
                                       PID7 |
                           Strong Democrat  |   3.854939   .4007531     9.62   0.000      3.06926    4.640618
                  Not very strong Democrat  |   2.047608   .2715741     7.54   0.000     1.515185    2.580031
                             Lean Democrat  |   3.892156   .5247848     7.42   0.000     2.863312       4.921
                           Lean Republican  |   -1.94257   .3119553    -6.23   0.000    -2.554161    -1.33098
                Not very strong Republican  |  -1.291251   .3007401    -4.29   0.000    -1.880854   -.7016481
                         Strong Republican  |  -2.875706   .3410227    -8.43   0.000    -3.544283   -2.207129
                                  Not sure  |  -.2390765   .6111645    -0.39   0.696    -1.437269    .9591157
                                            |
                                   FTWHITE5 |
                                      0/25  |   .7937579   .6709873     1.18   0.237    -.5217172    2.109233
                                     26/49  |   .9265164   .5130712     1.81   0.071    -.0793632    1.932396
                                   Missing  |  -.1157241   1.059355    -0.11   0.913    -2.192596    1.961148
                                     51/75  |   .4896838   .4354814     1.12   0.261    -.3640805    1.343448
                                     76/99  |  -.0819755   .4310397    -0.19   0.849    -.9270319    .7630809
                                       100  |  -.3650083   .5242547    -0.70   0.486    -1.392813    .6627966
                                            |
                                   FTBLACK5 |
                                      0/25  |   1.219687   .6243235     1.95   0.051    -.0043037    2.443677
                                     26/49  |   .4486482   .5294316     0.85   0.397     -.589306    1.486602
                                   Missing  |   .7670073   .9880514     0.78   0.438    -1.170074    2.704089
                                     51/75  |   .3556316   .4650325     0.76   0.444    -.5560679    1.267331
                                     76/99  |  -.2924415   .5151156    -0.57   0.570    -1.302329    .7174462
                                       100  |   .1211552   .6737479     0.18   0.857    -1.199732    1.442043
                                            |
                                   FTHISPN5 |
                                      0/25  |  -.1468762   .7396055    -0.20   0.843    -1.596878    1.303125
                                     26/49  |   -.425091   .4887332    -0.87   0.384    -1.383256    .5330739
                                   Missing  |   -.808751   .7581736    -1.07   0.286    -2.295156    .6776534
                                     51/75  |  -.2585303   .4297196    -0.60   0.547    -1.100998    .5839378
                                     76/99  |  -.3113339    .482614    -0.65   0.519    -1.257502    .6348343
                                       100  |  -.3563155   .5796937    -0.61   0.539    -1.492809    .7801779
                                            |
                                   FTASIAN5 |
                                      0/25  |    .338377   .7668851     0.44   0.659    -1.165107     1.84186
                                     26/49  |    1.41017   .5657329     2.49   0.013     .3010466    2.519293
                                   Missing  |  -.3665207   1.053862    -0.35   0.728    -2.432624    1.699583
                                     51/75  |   .0027625   .3683555     0.01   0.994     -.719401    .7249261
                                     76/99  |   .2875775   .4426003     0.65   0.516    -.5801433    1.155298
                                       100  |   .4917799   .5695515     0.86   0.388    -.6248297    1.608389
                                            |
                                     FTBLM5 |
                                      0/25  |  -1.441487   .4470803    -3.22   0.001    -2.317991   -.5649832
                                     26/49  |   .3312062   .4745172     0.70   0.485    -.5990879      1.2615
                                   Missing  |  -.8905598   .8041565    -1.11   0.268    -2.467114    .6859946
                                     51/75  |   1.869236   .4955905     3.77   0.000     .8976271    2.840844
                                     76/99  |   1.979323   .5230226     3.78   0.000     .9539332    3.004712
                                       100  |   3.310219   .7384355     4.48   0.000     1.862511    4.757927
                                            |
                                     FTGAY5 |
                                      0/25  |   .1515791   .4373358     0.35   0.729    -.7058207    1.008979
                                     26/49  |   .0774378   .4419848     0.18   0.861    -.7890764    .9439521
                                   Missing  |  -1.072217   .8531391    -1.26   0.209    -2.744802    .6003676
                                     51/75  |  -.0430528   .4171947    -0.10   0.918    -.8609658    .7748602
                                     76/99  |   .3551198   .4387738     0.81   0.418    -.5050993    1.215339
                                       100  |  -.4046699   .5912875    -0.68   0.494    -1.563893    .7545532
                                            |
                                   FTMUSLM5 |
                                      0/25  |  -.6605306   .3409291    -1.94   0.053    -1.328925    .0078633
                                     26/49  |   -.640099   .3524848    -1.82   0.069    -1.331148    .0509499
                                   Missing  |  -.2294216     .56658    -0.40   0.686    -1.340206    .8813624
                                     51/75  |  -.3699622    .329375    -1.12   0.261    -1.015704    .2757797
                                     76/99  |  -.6733838   .4126054    -1.63   0.103      -1.4823     .135532
                                       100  |  -.3868537   .6821912    -0.57   0.571    -1.724294    .9505868
                                            |
                                  FTPOLICE5 |
                                      0/25  |   1.105286   .5816814     1.90   0.057     -.035104    2.245677
                                     26/49  |   .3194831   .5421234     0.59   0.556    -.7433535     1.38232
                                   Missing  |   2.000643   .8995604     2.22   0.026     .2370487    3.764237
                                     51/75  |  -.4120577   .4257223    -0.97   0.333    -1.246689    .4225738
                                     76/99  |  -1.249317   .4306082    -2.90   0.004    -2.093528    -.405107
                                       100  |  -2.509765   .5071183    -4.95   0.000    -3.503974   -1.515556
                                            |
                                      _cons |  -.5632184   1.140721    -0.49   0.622     -2.79961    1.673174
-------------------------------------------------------------------------------------------------------------

. estimates store f33

. margins, atmeans at(FTIMMIG5 = (0 1 2 4 5 6)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1571762    .062197     2.53   0.012     .0710083    .2433441
          2  |   .5098678   .0974499     5.23   0.000     .3748605    .6448751
          3  |   .5438392   .0796906     6.82   0.000     .4334356    .6542427
          4  |   .5673665   .0512049    11.08   0.000     .4964271    .6383058
          5  |   .7507673   .0445783    16.84   0.000     .6890084    .8125262
          6  |   .8607868    .074208    11.60   0.000     .7579789    .9635948
------------------------------------------------------------------------------

. 
. *****************************************************************************************************************
> *
. * Figure 4. Relative measure [using Nov 2020 weights]
. *****************************************************************************************************************
> *
. 
. svyset [pw = weight_genpop_2020Nov]

Sampling weights: weight_genpop_2020Nov
             VCE: linearized
     Single unit: missing
        Strata 1: <one>
 Sampling unit 1: <observations>
           FPC 1: <zero>

. 
. svy: prop FTIMM3, level(83.4)
(running proportion on estimation sample)

Survey: Proportion estimation

Number of strata =     1                             Number of obs   = 4,943
Number of PSUs   = 4,943                             Population size = 4,943
                                                     Design df       = 4,942

----------------------------------------------------------------------------
                           |             Linearized            Logit
                           | Proportion   std. err.   [83.4% conf. interval]
---------------------------+------------------------------------------------
                    FTIMM3 |
       Cold to immigrants  |   .0993976   .0052909      .0923043    .1069718
Indifferent to immigrants  |   .0607556   .0039342      .0555284    .0664401
       Warm to immigrants  |   .0946211   .0047502      .0882422    .1014099
                  Missing  |   .0831023    .005625      .0756345    .0912348
                 Residual  |   .6621233   .0083631      .6504419    .6736103
----------------------------------------------------------------------------

. 
. * No controls
. 
. svy: logit VOTEBT i.FTIMM3
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(4, 4368)      =      52.38
                                                  Prob > F        =     0.0000

--------------------------------------------------------------------------------------------
                           |             Linearized
                    VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------+----------------------------------------------------------------
                    FTIMM3 |
Indifferent to immigrants  |   1.189304   .1987692     5.98   0.000     .7996153    1.578992
       Warm to immigrants  |   2.756756   .2008837    13.72   0.000     2.362922     3.15059
                  Missing  |   1.501559   .2117598     7.09   0.000     1.086403    1.916716
                 Residual  |   1.739824    .151073    11.52   0.000     1.443644    2.036003
                           |
                     _cons |  -1.536011   .1444157   -10.64   0.000    -1.819139   -1.252883
--------------------------------------------------------------------------------------------

. margins, atmeans at(FTIMM3 = (1 2 3)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1771158    .021048     8.41   0.000     .1479559    .2062758
          2  |    .414181   .0331384    12.50   0.000      .368271     .460091
          3  |   .7721946   .0245635    31.44   0.000     .7381643    .8062249
------------------------------------------------------------------------------

. 
. * Controls for demographics
. 
. svy: logit VOTEBT ib2.FTIMM3  i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME i.ATTEND i.STATE
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(80, 4292)     =       9.32
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                     FTIMM3 |
                        Cold to immigrants  |  -1.324077   .2375352    -5.57   0.000    -1.789767   -.8583879
                        Warm to immigrants  |   1.490853   .2195438     6.79   0.000     1.060436     1.92127
                                   Missing  |   .0962947   .2459547     0.39   0.695    -.3859012    .5784907
                                  Residual  |   .4632881   .1731938     2.67   0.008     .1237404    .8028357
                                            |
                                     GENDER |
                                    Female  |   .6663422   .0849496     7.84   0.000      .499798    .8328865
                                            |
                                       RACE |
                                     Black  |   2.728151   .2160561    12.63   0.000     2.304572    3.151731
                                  Hispanic  |   1.018055   .1573559     6.47   0.000     .7095581    1.326553
                                     Asian  |   .7555177   .3110522     2.43   0.015     .1456977    1.365338
                                     Other  |   .2194506   .1904385     1.15   0.249    -.1539053    .5928065
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.3588184   .1677023    -2.14   0.032       -.6876   -.0300369
                                 Age 46/60  |  -.4657276   .1631561    -2.85   0.004    -.7855962    -.145859
                                   Age 61+  |  -.2647639   .1648634    -1.61   0.108    -.5879797     .058452
                                            |
                                       EDUC |
                      High school graduate  |  -.3959186   .2911123    -1.36   0.174    -.9666463    .1748091
                              Some college  |  -.2292272   .2929115    -0.78   0.434    -.8034822    .3450277
                                    2-year  |  -.1049453   .3078373    -0.34   0.733    -.7084624    .4985718
                                    4-year  |   .0477149   .2967045     0.16   0.872    -.5339763     .629406
                                 Post-grad  |   .7046641   .3078951     2.29   0.022     .1010337    1.308295
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .0609194   .1357129     0.45   0.654    -.2051467    .3269854
                                   Widowed  |   .1112359   .1635847     0.68   0.497     -.209473    .4319448
                             Never married  |   .4977579   .1235537     4.03   0.000       .25553    .7399858
                Domestic/civil partnership  |   .6051348    .247651     2.44   0.015     .1196134    1.090656
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.1119644   .1367919    -0.82   0.413     -.380146    .1562171
                                 $70k-$99k  |  -.2255133   .1631903    -1.38   0.167     -.545449    .0944225
                               $100k-$149k  |  -.1338379   .1709677    -0.78   0.434    -.4690212    .2013454
                                   $150k +  |  -.0668489   .1916359    -0.35   0.727    -.4425524    .3088546
                         Prefer to not say  |  -.4785611   .1698566    -2.82   0.005    -.8115662    -.145556
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .6680593   .1328732     5.03   0.000     .4075605     .928558
                                    Seldom  |   .8088473   .1254935     6.45   0.000     .5628164    1.054878
                                     Never  |   1.553601   .1174858    13.22   0.000     1.323269    1.783933
                      Don't know / Skipped  |   .4656463   .3385399     1.38   0.169    -.1980634    1.129356
                                            |
                                      STATE |
                                    Alaska  |   .5891635   .6374234     0.92   0.355    -.6605095    1.838837
                                   Arizona  |  -.5202459   .4692854    -1.11   0.268    -1.440283    .3997912
                                  Arkansas  |  -.7935819   .5048714    -1.57   0.116    -1.783386    .1962219
                                California  |  -.1391714   .3925299    -0.35   0.723    -.9087289    .6303861
                                  Colorado  |  -.1933644   .4695856    -0.41   0.681     -1.11399    .7272614
                               Connecticut  |  -.3221957   .5434296    -0.59   0.553    -1.387593    .7432017
                                  Delaware  |  -.1140601   .8644136    -0.13   0.895    -1.808749    1.580629
                      District of Columbia  |    1.13727   1.266108     0.90   0.369    -1.344944    3.619484
                                   Florida  |  -.9875073   .4070104    -2.43   0.015    -1.785454   -.1895606
                                   Georgia  |  -.8666496   .4481563    -1.93   0.053    -1.745263    .0119639
                                    Hawaii  |   -.286079   .8117711    -0.35   0.725    -1.877562    1.305404
                                     Idaho  |  -.4645392   .5140377    -0.90   0.366    -1.472314    .5432353
                                  Illinois  |  -.3005471   .4167126    -0.72   0.471    -1.117515    .5164209
                                   Indiana  |  -.1232777   .4459327    -0.28   0.782    -.9975318    .7509764
                                      Iowa  |   .0133323   .4861791     0.03   0.978    -.9398252    .9664898
                                    Kansas  |  -.1554284   .5335875    -0.29   0.771     -1.20153    .8906735
                                  Kentucky  |  -.4930344   .5467663    -0.90   0.367    -1.564974    .5789047
                                 Louisiana  |  -.6750565   .4948392    -1.36   0.173    -1.645192    .2950792
                                     Maine  |   .5944107   .5616389     1.06   0.290    -.5066863    1.695508
                                  Maryland  |   .2194456   .4721606     0.46   0.642    -.7062284     1.14512
                             Massachusetts  |   .0161677   .4723466     0.03   0.973     -.909871    .9422063
                                  Michigan  |  -.4780826    .436749    -1.09   0.274    -1.334332    .3781668
                                 Minnesota  |  -.4231807   .4590111    -0.92   0.357    -1.323075    .4767137
                               Mississippi  |  -.8281685   .5358557    -1.55   0.122    -1.878717    .2223803
                                  Missouri  |  -.7422029   .4797446    -1.55   0.122    -1.682745    .1983395
                                   Montana  |  -.7645646   .6357594    -1.20   0.229    -2.010975    .4818461
                                  Nebraska  |  -.9187085   .6113708    -1.50   0.133    -2.117305    .2798881
                                    Nevada  |  -1.034794   .5838315    -1.77   0.076      -2.1794    .1098114
                             New Hampshire  |  -.5294982   .6044382    -0.88   0.381    -1.714503     .655507
                                New Jersey  |   -.600692   .4188118    -1.43   0.152    -1.421775    .2203915
                                New Mexico  |  -.7930694   .5980384    -1.33   0.185    -1.965528    .3793889
                                  New York  |   .2177142   .4052481     0.54   0.591    -.5767775    1.012206
                            North Carolina  |  -.4403666   .4524488    -0.97   0.330    -1.327396    .4466623
                              North Dakota  |  -.3457582   .8437405    -0.41   0.682    -1.999917    1.308401
                                      Ohio  |  -.0520986   .4359194    -0.12   0.905    -.9067216    .8025245
                                  Oklahoma  |  -1.154309   .5243288    -2.20   0.028     -2.18226   -.1263591
                                    Oregon  |  -.1571134   .4830955    -0.33   0.745    -1.104226    .7899987
                              Pennsylvania  |  -.2043931   .3979812    -0.51   0.608    -.9846379    .5758518
                              Rhode Island  |    .127312   .8028544     0.16   0.874     -1.44669    1.701314
                            South Carolina  |  -.4540725   .4793167    -0.95   0.344    -1.393776    .4856312
                              South Dakota  |  -1.668665   .7002723    -2.38   0.017    -3.041553   -.2957759
                                 Tennessee  |  -.7877095    .463921    -1.70   0.090     -1.69723    .1218108
                                     Texas  |   -.192205   .4075761    -0.47   0.637    -.9912608    .6068508
                                      Utah  |  -.1310136   .5793815    -0.23   0.821    -1.266895    1.004868
                                   Vermont  |   .6509374   .8001845     0.81   0.416    -.9178298    2.219705
                                  Virginia  |  -.1345868    .429044    -0.31   0.754    -.9757306     .706557
                                Washington  |   .0256776   .4387361     0.06   0.953    -.8344675    .8858228
                             West Virginia  |  -.3382171   .5640691    -0.60   0.549    -1.444078    .7676442
                                 Wisconsin  |  -.3278869   .4327662    -0.76   0.449    -1.176328    .5205541
                                   Wyoming  |   .2853163   .6238664     0.46   0.647    -.9377781    1.508411
                                            |
                                      _cons |  -1.143061    .536977    -2.13   0.033    -2.195808   -.0903135
-------------------------------------------------------------------------------------------------------------

. estimates store f41

. margins, atmeans at(FTIMM3 = (1 2 3)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1815833   .0250086     7.26   0.000     .1469363    .2162302
          2  |   .4547293    .041608    10.93   0.000     .3970855    .5123731
          3  |   .7873915   .0250777    31.40   0.000     .7526487    .8221342
------------------------------------------------------------------------------

. 
. * Controls for demographics and partisanship
. 
. svy: logit VOTEBT ib2.FTIMM3  i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME i.ATTEND i.STATE ib4.PID7
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(87, 4285)     =      14.03
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                     FTIMM3 |
                        Cold to immigrants  |  -1.532311   .4108104    -3.73   0.000    -2.337708   -.7269146
                        Warm to immigrants  |   1.415775   .3162124     4.48   0.000     .7958382    2.035711
                                   Missing  |  -.1365494   .3840667    -0.36   0.722    -.8895148     .616416
                                  Residual  |   .3559121   .2537639     1.40   0.161    -.1415937    .8534179
                                            |
                                     GENDER |
                                    Female  |   .6336349   .1475496     4.29   0.000     .3443629    .9229069
                                            |
                                       RACE |
                                     Black  |   1.577846   .3474437     4.54   0.000     .8966805    2.259012
                                  Hispanic  |   1.080843   .2594987     4.17   0.000     .5720941    1.589592
                                     Asian  |   1.018048   .3886094     2.62   0.009     .2561769     1.77992
                                     Other  |   .1813583   .2348962     0.77   0.440    -.2791573     .641874
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.1933204   .2902236    -0.67   0.505    -.7623058    .3756649
                                 Age 46/60  |  -.1701799   .2875372    -0.59   0.554    -.7338986    .3935388
                                   Age 61+  |  -.1436896   .2945078    -0.49   0.626    -.7210741    .4336949
                                            |
                                       EDUC |
                      High school graduate  |   .3551868   .5684498     0.62   0.532    -.7592629    1.469637
                              Some college  |   .1878797   .5523393     0.34   0.734    -.8949853    1.270745
                                    2-year  |  -.1423854    .580661    -0.25   0.806    -1.280775    .9960044
                                    4-year  |   .4057794   .5710711     0.71   0.477    -.7138095    1.525368
                                 Post-grad  |   .8924451   .5893049     1.51   0.130    -.2628911    2.047781
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .1632546   .2462808     0.66   0.507    -.3195805    .6460897
                                   Widowed  |     .18876   .2665066     0.71   0.479     -.333728     .711248
                             Never married  |   .8524143   .2062228     4.13   0.000     .4481131    1.256715
                Domestic/civil partnership  |   .6064653   .5088254     1.19   0.233    -.3910905    1.604021
                                            |
                                   HHINCOME |
                                 $30k-$69k  |  -.0058566   .2309292    -0.03   0.980     -.458595    .4468818
                                 $70k-$99k  |   .2896244   .2630908     1.10   0.271    -.2261669    .8054156
                               $100k-$149k  |    .160382    .311312     0.52   0.606    -.4499474    .7707113
                                   $150k +  |   .7758211    .351152     2.21   0.027     .0873853    1.464257
                         Prefer to not say  |  -.1927523   .2888574    -0.67   0.505    -.7590593    .3735546
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .4438124    .249496     1.78   0.075    -.0453263    .9329511
                                    Seldom  |   .7044679   .2224614     3.17   0.002     .2683308    1.140605
                                     Never  |   .9631871   .2268478     4.25   0.000     .5184504    1.407924
                      Don't know / Skipped  |   .7581282   .3726028     2.03   0.042     .0276379    1.488618
                                            |
                                      STATE |
                                    Alaska  |  -.2993254   .9451786    -0.32   0.751    -2.152355    1.553704
                                   Arizona  |  -1.189893   .7193928    -1.65   0.098    -2.600267    .2204817
                                  Arkansas  |   .0155576   .8024432     0.02   0.985    -1.557638    1.588753
                                California  |  -.9450076   .6517108    -1.45   0.147    -2.222691    .3326759
                                  Colorado  |   .0042884   .6705187     0.01   0.995    -1.310268    1.318845
                               Connecticut  |  -.5188132    .737816    -0.70   0.482    -1.965307    .9276801
                                  Delaware  |   .1485654   1.258364     0.12   0.906    -2.318466    2.615597
                      District of Columbia  |  -.9971123   2.466517    -0.40   0.686    -5.832736    3.838511
                                   Florida  |  -1.414041   .6164335    -2.29   0.022    -2.622563   -.2055191
                                   Georgia  |  -.7220417   .6739477    -1.07   0.284    -2.043321    .5992373
                                    Hawaii  |   .2798285   .9634648     0.29   0.771    -1.609051    2.168708
                                     Idaho  |  -.7268651   .7078837    -1.03   0.305    -2.114676    .6609458
                                  Illinois  |  -1.018564   .6544223    -1.56   0.120    -2.301564    .2644351
                                   Indiana  |  -.7804129   .7137436    -1.09   0.274    -2.179712    .6188863
                                      Iowa  |  -.3301531   .7502524    -0.44   0.660    -1.801028    1.140722
                                    Kansas  |   .8202219   .7396985     1.11   0.268    -.6299621    2.270406
                                  Kentucky  |   -2.24553    .845731    -2.66   0.008    -3.903592   -.5874688
                                 Louisiana  |  -1.013093   .7687147    -1.32   0.188    -2.520163    .4939777
                                     Maine  |  -1.077902   1.138368    -0.95   0.344    -3.309681    1.153876
                                  Maryland  |  -.6594118   .7337904    -0.90   0.369    -2.098013    .7791893
                             Massachusetts  |  -.6871804   .6785304    -1.01   0.311    -2.017444     .643083
                                  Michigan  |  -1.946741   .8371419    -2.33   0.020    -3.587963   -.3055184
                                 Minnesota  |  -.3442622   .7866198    -0.44   0.662    -1.886436    1.197911
                               Mississippi  |  -.6529091   .9227641    -0.71   0.479    -2.461994    1.156176
                                  Missouri  |  -.9058589   .7360146    -1.23   0.218    -2.348821    .5371027
                                   Montana  |  -1.827131   .7115898    -2.57   0.010    -3.222208   -.4320541
                                  Nebraska  |  -1.934723   .9634654    -2.01   0.045    -3.823603   -.0458423
                                    Nevada  |  -2.572996    .712179    -3.61   0.000    -3.969228   -1.176764
                             New Hampshire  |  -.9554571   .8791889    -1.09   0.277    -2.679113    .7681988
                                New Jersey  |  -1.648071   .7426247    -2.22   0.027    -3.103992   -.1921503
                                New Mexico  |  -1.952926   .8540352    -2.29   0.022    -3.627268   -.2785842
                                  New York  |  -.5306315   .6758885    -0.79   0.432    -1.855715    .7944525
                            North Carolina  |  -1.904601   .7750875    -2.46   0.014    -3.424165   -.3850365
                              North Dakota  |  -1.305699   .8180102    -1.60   0.111    -2.909413    .2980158
                                      Ohio  |  -1.317036    .709431    -1.86   0.063     -2.70788    .0738087
                                  Oklahoma  |  -1.382671    1.35067    -1.02   0.306    -4.030668    1.265327
                                    Oregon  |  -1.071172   .8955805    -1.20   0.232    -2.826964    .6846194
                              Pennsylvania  |  -1.571386   .6573261    -2.39   0.017    -2.860078   -.2826934
                              Rhode Island  |  -.4579478   1.531783    -0.30   0.765     -3.46102    2.545124
                            South Carolina  |  -.3385548    .821107    -0.41   0.680    -1.948341    1.271231
                              South Dakota  |  -1.938952   1.273033    -1.52   0.128    -4.434741    .5568376
                                 Tennessee  |  -.8883792    .749452    -1.19   0.236    -2.357685    .5809265
                                     Texas  |  -.6039211   .6599207    -0.92   0.360      -1.8977    .6898579
                                      Utah  |   .1553727   .7480753     0.21   0.835    -1.311234    1.621979
                                   Vermont  |    .293887   .9507515     0.31   0.757    -1.570068    2.157842
                                  Virginia  |  -.5346853     .73794    -0.72   0.469    -1.981422    .9120511
                                Washington  |  -.4262657    .673248    -0.63   0.527    -1.746173    .8936417
                             West Virginia  |   -1.57278   1.133726    -1.39   0.165    -3.795457    .6498975
                                 Wisconsin  |  -.8936598   .7463304    -1.20   0.231    -2.356846    .5695261
                                   Wyoming  |   .6905334   .8644999     0.80   0.424    -1.004325    2.385391
                                            |
                                       PID7 |
                           Strong Democrat  |   4.355738   .2892464    15.06   0.000     3.788669    4.922808
                  Not very strong Democrat  |   2.245224    .208342    10.78   0.000     1.836768     2.65368
                             Lean Democrat  |   3.949481   .4116322     9.59   0.000     3.142473    4.756488
                           Lean Republican  |   -2.80714   .3079334    -9.12   0.000    -3.410846   -2.203435
                Not very strong Republican  |  -1.647396   .2163151    -7.62   0.000    -2.071483   -1.223309
                         Strong Republican  |   -3.65922   .3157289   -11.59   0.000    -4.278208   -3.040231
                                  Not sure  |   .2331044   .4775813     0.49   0.626     -.703197    1.169406
                                            |
                                      _cons |  -1.429865    .854927    -1.67   0.094    -3.105956     .246225
-------------------------------------------------------------------------------------------------------------

. estimates store f42

. margins, atmeans at(PID7 = 4 FTIMM3 = (1 2 3)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1109174   .0348354     3.18   0.001     .0626564    .1591784
          2  |   .3660748    .061243     5.98   0.000     .2812286     .450921
          3  |   .7040548   .0463521    15.19   0.000     .6398385     .768271
------------------------------------------------------------------------------

. 
. * Controls for demographics, partisanship, and other groups
. 
. svy: logit VOTEBT ib2.FTIMM3  i.GENDER i.RACE i.AGEGRP i.EDUC i.MARITAL i.HHINCOME i.ATTEND i.STATE ib4.PID7 ib2.
> FTBLM5 ib2.FTGAY5 ib2.FTMUSLM5 ib2.FTPOLICE5
(running logit on estimation sample)

Survey: Logistic regression

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
                                                  Design df       =      4,371
                                                  F(111, 4261)    =       9.09
                                                  Prob > F        =     0.0000

-------------------------------------------------------------------------------------------------------------
                                            |             Linearized
                                     VOTEBT | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------------+----------------------------------------------------------------
                                     FTIMM3 |
                        Cold to immigrants  |  -1.064711   .4570361    -2.33   0.020    -1.960733   -.1686884
                        Warm to immigrants  |   .9616786   .4365149     2.20   0.028     .1058882    1.817469
                                   Missing  |  -.4436111   .6660554    -0.67   0.505    -1.749417     .862195
                                  Residual  |   .0328946   .3598383     0.09   0.927    -.6725708    .7383601
                                            |
                                     GENDER |
                                    Female  |   .4390538   .1915203     2.29   0.022     .0635768    .8145307
                                            |
                                       RACE |
                                     Black  |   .4651763   .3906188     1.19   0.234    -.3006346    1.230987
                                  Hispanic  |   1.109114   .2840385     3.90   0.000     .5522548    1.665974
                                     Asian  |   .6056127   .5658513     1.07   0.285    -.5037427    1.714968
                                     Other  |   .2392374   .2414748     0.99   0.322    -.2341757    .7126504
                                            |
                                     AGEGRP |
                                 Age 31/45  |  -.0440597   .3750169    -0.12   0.906    -.7792829    .6911635
                                 Age 46/60  |   .5467067   .3548047     1.54   0.123    -.1488903    1.242304
                                   Age 61+  |   .8776079   .3779364     2.32   0.020     .1366611    1.618555
                                            |
                                       EDUC |
                      High school graduate  |  -.2638894   .7180949    -0.37   0.713    -1.671719    1.143941
                              Some college  |  -.5128749   .7155599    -0.72   0.474    -1.915735    .8899853
                                    2-year  |  -.5975243   .7581844    -0.79   0.431     -2.08395    .8889014
                                    4-year  |  -.2682739   .7259758    -0.37   0.712    -1.691554    1.155007
                                 Post-grad  |   .0048117    .750189     0.01   0.995    -1.465939    1.475562
                                            |
                                    MARITAL |
                      Separated / Divorced  |   .1932954   .2792339     0.69   0.489    -.3541445    .7407354
                                   Widowed  |   .2066773   .3599052     0.57   0.566    -.4989192    .9122739
                             Never married  |   .7920401   .2736577     2.89   0.004     .2555322    1.328548
                Domestic/civil partnership  |   .4604009   .8509061     0.54   0.588    -1.207806    2.128608
                                            |
                                   HHINCOME |
                                 $30k-$69k  |   .4816729   .2924559     1.65   0.100    -.0916889    1.055035
                                 $70k-$99k  |   .7796785   .3399115     2.29   0.022     .1132797    1.446077
                               $100k-$149k  |    .676125   .3452399     1.96   0.050    -.0007202     1.35297
                                   $150k +  |   1.301924   .4606439     2.83   0.005     .3988287     2.20502
                         Prefer to not say  |   .2329834   .3932125     0.59   0.554    -.5379124    1.003879
                                            |
                                     ATTEND |
Once or twice a month / A few times a year  |   .5044107   .3038194     1.66   0.097    -.0912294    1.100051
                                    Seldom  |   .7738395   .3006503     2.57   0.010     .1844125    1.363267
                                     Never  |   1.186907   .2654253     4.47   0.000     .6665385    1.707275
                      Don't know / Skipped  |   .4739699   .5810174     0.82   0.415    -.6651186    1.613058
                                            |
                                      STATE |
                                    Alaska  |  -.5159785   .9091045    -0.57   0.570    -2.298284    1.266327
                                   Arizona  |  -1.164238   .6015395    -1.94   0.053     -2.34356    .0150846
                                  Arkansas  |   .6278738   .7429281     0.85   0.398    -.8286418    2.084389
                                California  |  -1.277764   .6185235    -2.07   0.039    -2.490384   -.0651446
                                  Colorado  |  -.4096047   .6211105    -0.66   0.510    -1.627296    .8080867
                               Connecticut  |   -.382463   .6728181    -0.57   0.570    -1.701528    .9366015
                                  Delaware  |   .4576519   .8998939     0.51   0.611    -1.306596      2.2219
                      District of Columbia  |  -.0704256    1.92065    -0.04   0.971    -3.835873    3.695022
                                   Florida  |  -1.695987   .5542945    -3.06   0.002    -2.782685   -.6092889
                                   Georgia  |  -.9000816   .5761062    -1.56   0.118    -2.029542    .2293784
                                    Hawaii  |   -.260481   .9165148    -0.28   0.776    -2.057315    1.536353
                                     Idaho  |  -1.028691   .8495247    -1.21   0.226     -2.69419    .6368082
                                  Illinois  |  -.9252018   .6229009    -1.49   0.138    -2.146403    .2959996
                                   Indiana  |  -.8811757   .6897989    -1.28   0.202    -2.233531    .4711799
                                      Iowa  |  -.7831155   .8969421    -0.87   0.383    -2.541577    .9753457
                                    Kansas  |   .7588885   .7090034     1.07   0.285    -.6311175    2.148895
                                  Kentucky  |   -2.36217   1.217661    -1.94   0.052    -4.749403    .0250629
                                 Louisiana  |  -1.221554   .7371802    -1.66   0.098    -2.666801    .2236923
                                     Maine  |  -2.631519   1.215985    -2.16   0.031    -5.015465   -.2475723
                                  Maryland  |  -1.019583   .6518946    -1.56   0.118    -2.297627    .2584605
                             Massachusetts  |  -.7042283   .7101497    -0.99   0.321    -2.096482    .6880251
                                  Michigan  |  -2.683618   .7876218    -3.41   0.001    -4.227756    -1.13948
                                 Minnesota  |   -1.13274   .8912393    -1.27   0.204     -2.88002    .6145411
                               Mississippi  |  -1.345776   1.003892    -1.34   0.180    -3.313913    .6223609
                                  Missouri  |   -.689916   .6286618    -1.10   0.273    -1.922412    .5425797
                                   Montana  |  -3.514061   .9013559    -3.90   0.000    -5.281176   -1.746947
                                  Nebraska  |  -2.076791   1.533571    -1.35   0.176    -5.083368    .9297849
                                    Nevada  |   -2.78572   .6943502    -4.01   0.000    -4.146999   -1.424442
                             New Hampshire  |  -1.224409   .8250616    -1.48   0.138    -2.841948    .3931296
                                New Jersey  |  -2.391983   .6626229    -3.61   0.000    -3.691059   -1.092906
                                New Mexico  |  -1.618829   1.087376    -1.49   0.137    -3.750637    .5129786
                                  New York  |  -.8973055   .5659862    -1.59   0.113    -2.006925    .2123142
                            North Carolina  |  -2.272111   .7398148    -3.07   0.002    -3.722523   -.8216989
                              North Dakota  |  -.3037121   .8966843    -0.34   0.735    -2.061668    1.454244
                                      Ohio  |  -1.081076   .6314787    -1.71   0.087    -2.319095    .1569418
                                  Oklahoma  |  -1.900514   .7933811    -2.40   0.017    -3.455943   -.3450852
                                    Oregon  |  -1.072335   .8286896    -1.29   0.196    -2.696987    .5523163
                              Pennsylvania  |  -1.423995    .563031    -2.53   0.011    -2.527822   -.3201692
                              Rhode Island  |  -.6890978   1.419191    -0.49   0.627    -3.471432    2.093236
                            South Carolina  |  -1.492803   .9673998    -1.54   0.123    -3.389397    .4037914
                              South Dakota  |  -2.041078   1.196563    -1.71   0.088    -4.386947    .3047915
                                 Tennessee  |  -1.693534   .8526412    -1.99   0.047    -3.365142   -.0219248
                                     Texas  |  -.8948236   .6554938    -1.37   0.172    -2.179924    .3902765
                                      Utah  |  -.1552308   .6493694    -0.24   0.811    -1.428324    1.117862
                                   Vermont  |    .455707   1.004163     0.45   0.650    -1.512961    2.424375
                                  Virginia  |  -.9744513   .8673753    -1.12   0.261    -2.674947    .7260439
                                Washington  |  -.1420799   .5963708    -0.24   0.812    -1.311269    1.027109
                             West Virginia  |   .0582972   .9631652     0.06   0.952    -1.829995    1.946589
                                 Wisconsin  |   -.803862   .5760065    -1.40   0.163    -1.933127    .3254026
                                   Wyoming  |   .0874775   .7827422     0.11   0.911    -1.447094    1.622049
                                            |
                                       PID7 |
                           Strong Democrat  |   3.789029   .3614164    10.48   0.000      3.08047    4.497589
                  Not very strong Democrat  |   2.001194   .2594681     7.71   0.000     1.492505    2.509883
                             Lean Democrat  |   3.593379   .4850154     7.41   0.000     2.642503    4.544255
                           Lean Republican  |  -1.953138   .3266437    -5.98   0.000    -2.593525   -1.312751
                Not very strong Republican  |  -1.309456   .2919819    -4.48   0.000    -1.881889   -.7370237
                         Strong Republican  |  -2.798468   .3395184    -8.24   0.000    -3.464096    -2.13284
                                  Not sure  |  -.3657006   .6845936    -0.53   0.593    -1.707851    .9764498
                                            |
                                     FTBLM5 |
                                      0/25  |  -1.371483   .3765208    -3.64   0.000    -2.109654   -.6333112
                                     26/49  |   .3778511   .4094231     0.92   0.356    -.4248256    1.180528
                                   Missing  |  -.5817698   .6637591    -0.88   0.381    -1.883074    .7195345
                                     51/75  |    1.65582   .4168801     3.97   0.000     .8385237    2.473116
                                     76/99  |   1.802084   .4573586     3.94   0.000     .9054293    2.698739
                                       100  |   3.184152   .7109169     4.48   0.000     1.790394    4.577909
                                            |
                                     FTGAY5 |
                                      0/25  |    .168395   .4368754     0.39   0.700    -.6881022    1.024892
                                     26/49  |    .348199   .4108037     0.85   0.397    -.4571845    1.153582
                                   Missing  |  -.7148384   .7978499    -0.90   0.370    -2.279029    .8493517
                                     51/75  |   .1288873    .369284     0.35   0.727    -.5950966    .8528712
                                     76/99  |   .5067291    .401601     1.26   0.207    -.2806124    1.294071
                                       100  |   -.170209   .5928643    -0.29   0.774    -1.332524    .9921055
                                            |
                                   FTMUSLM5 |
                                      0/25  |  -.6924634   .3226295    -2.15   0.032    -1.324981   -.0599461
                                     26/49  |  -.4848609   .3243046    -1.50   0.135    -1.120662    .1509405
                                   Missing  |  -.2475796   .5533402    -0.45   0.655    -1.332407    .8372476
                                     51/75  |  -.3080828   .3018156    -1.02   0.307    -.8997943    .2836287
                                     76/99  |  -.5755657   .3606675    -1.60   0.111    -1.282657    .1315255
                                       100  |    .515396    .596892     0.86   0.388    -.6548149    1.685607
                                            |
                                  FTPOLICE5 |
                                      0/25  |   1.331534   .5951558     2.24   0.025     .1647267    2.498341
                                     26/49  |   .5427067   .5091538     1.07   0.287    -.4554929    1.540906
                                   Missing  |   2.006104   .8410231     2.39   0.017     .3572722    3.654935
                                     51/75  |  -.1926335   .3889442    -0.50   0.620    -.9551613    .5698943
                                     76/99  |  -1.202909   .3915805    -3.07   0.002    -1.970605   -.4352128
                                       100  |  -2.465799   .4672579    -5.28   0.000    -3.381861   -1.549737
                                            |
                                      _cons |  -.6369905   1.090554    -0.58   0.559    -2.775029    1.501048
-------------------------------------------------------------------------------------------------------------

. estimates store f43

. margins, atmeans at(FTIMM3 = (1 2 3)) noatlegend level(83.4)

Adjusted predictions

Number of strata =     1                          Number of obs   =      4,372
Number of PSUs   = 4,372                          Population size = 4,174.2252
Model VCE: Linearized                             Design df       =      4,371

Expression: Pr(VOTEBT), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|   [83.4% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .3573528   .0714898     5.00   0.000     .2583106     .456395
          2  |   .6172373   .0825029     7.48   0.000     .5029376    .7315371
          3  |   .8083799   .0457739    17.66   0.000     .7449645    .8717952
------------------------------------------------------------------------------

. 
. // esttab f41 f42 f43 using regression_output.rtf, b(%99.2f) se(%99.2f) starlevels(* 0.05) r2 ar2 pr2 nogaps labe
> l onecell replace
. 
end of do-file
